{ "cells": [ { "cell_type": "markdown", "id": "26f73182", "metadata": {}, "source": [ "# Introduction to Scikit-Learn\n", "\n", "Scikit-Learn (sklearn) is a powerful Python package for machine learning. The goals of this tutorial are:\n", "\n", "1. To learn how to use Scikit-Learn to implement machine learning models.\n", "2. To understand the general structure of using the Scikit-Learn API.\n", "\n", "The main framework for implementing machine learning models in sklearn are:\n", "\n", "1. Import the sklearn objects you need for the code\n", "2. Prepare a set of preprocessed (namely cleaned and scaled) data to give your model.\n", "3. Create the model object in your code.\n", "4. Use the model object to train your model using the appropriate training method (usually `fit()`)\n", "5. Apply model to data that the model has not seen (test data) using the appropriate prediction/transformation method (usually `predict()`)\n", "\n", "Understanding this structure and the methods within the sklearn objects that accomplish this are all you need in order to work with sklearn.\n", "\n", "In this tutorial we will cover features of sklearn that allow you to:\n", "\n", "- Load and preprocess data\n", "- Implement supervised learning models\n", "- Implement unsupervised learning models\n", "\n", "This notebook introduces these concepts with example code cells. Attendees are expected to follow along and execute the code cells themselves. I will explain what each of the commands do in the code blocks. \n", "\n", "I have included a few practice examples at the end of the tutorial." ] }, { "cell_type": "code", "execution_count": 1, "id": "3944fa42", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1.3.0\n" ] } ], "source": [ "# Import sklearn and print the version\n", "import sklearn\n", "print(sklearn.__version__)" ] }, { "cell_type": "markdown", "id": "6a9d3fc2", "metadata": {}, "source": [ "## Data preprocessing\n", "\n", "Data preprocessing is an essential step before applying any machine learning algorithm. In general, you are not handed a ready-to-use dataset. Datasets often contain incorrect data, missing data, and data with different scales adn types. \n", "\n", "Before you can extract useful information from the data through a machine learnign algorithm, you will need to preprocess the data. In this section we will demonstrate the following topics:\n", "\n", "- Loading datasets\n", "\n", " - Toy datasets\n", " - External datasets\n", " - Generated datasets\n", " - Real world dataset\n", " \n", "- Exploratory data analysis\n", "\n", " - Pandas tools\n", " - Basic visualization\n", " \n", "- Test train splits\n", "\n", "- Scaling datasets\n", "\n", " - Scaler object\n", " - Min-max scaling\n", " - Standardization" ] }, { "cell_type": "markdown", "id": "e3f9f7a8", "metadata": {}, "source": [ "### Toy datasets\n", "\n", "Scikit learn provides some built in toy datasets. There is an easy API call to load these datasets. Scikit-learn's toy datasets make it easy to test out many kinds of machine learning algorithms. The list of datasets is at this [link](https://scikit-learn.org/stable/datasets/toy_dataset.html#toy-datasets). The following code cell shows how to import a built-in toy dataset." ] }, { "cell_type": "code", "execution_count": 2, "id": "71730686", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'data': array([[5.1, 3.5, 1.4, 0.2],\n", " [4.9, 3. , 1.4, 0.2],\n", " [4.7, 3.2, 1.3, 0.2],\n", " [4.6, 3.1, 1.5, 0.2],\n", " [5. , 3.6, 1.4, 0.2],\n", " [5.4, 3.9, 1.7, 0.4],\n", " [4.6, 3.4, 1.4, 0.3],\n", " [5. , 3.4, 1.5, 0.2],\n", " [4.4, 2.9, 1.4, 0.2],\n", " [4.9, 3.1, 1.5, 0.1],\n", " [5.4, 3.7, 1.5, 0.2],\n", " [4.8, 3.4, 1.6, 0.2],\n", " [4.8, 3. , 1.4, 0.1],\n", " [4.3, 3. , 1.1, 0.1],\n", " [5.8, 4. , 1.2, 0.2],\n", " [5.7, 4.4, 1.5, 0.4],\n", " [5.4, 3.9, 1.3, 0.4],\n", " [5.1, 3.5, 1.4, 0.3],\n", " [5.7, 3.8, 1.7, 0.3],\n", " [5.1, 3.8, 1.5, 0.3],\n", " [5.4, 3.4, 1.7, 0.2],\n", " [5.1, 3.7, 1.5, 0.4],\n", " [4.6, 3.6, 1. , 0.2],\n", " [5.1, 3.3, 1.7, 0.5],\n", " [4.8, 3.4, 1.9, 0.2],\n", " [5. , 3. , 1.6, 0.2],\n", " [5. , 3.4, 1.6, 0.4],\n", " [5.2, 3.5, 1.5, 0.2],\n", " [5.2, 3.4, 1.4, 0.2],\n", " [4.7, 3.2, 1.6, 0.2],\n", " [4.8, 3.1, 1.6, 0.2],\n", " [5.4, 3.4, 1.5, 0.4],\n", " [5.2, 4.1, 1.5, 0.1],\n", " [5.5, 4.2, 1.4, 0.2],\n", " [4.9, 3.1, 1.5, 0.2],\n", " [5. , 3.2, 1.2, 0.2],\n", " [5.5, 3.5, 1.3, 0.2],\n", " [4.9, 3.6, 1.4, 0.1],\n", " [4.4, 3. , 1.3, 0.2],\n", " [5.1, 3.4, 1.5, 0.2],\n", " [5. , 3.5, 1.3, 0.3],\n", " [4.5, 2.3, 1.3, 0.3],\n", " [4.4, 3.2, 1.3, 0.2],\n", " [5. , 3.5, 1.6, 0.6],\n", " [5.1, 3.8, 1.9, 0.4],\n", " [4.8, 3. , 1.4, 0.3],\n", " [5.1, 3.8, 1.6, 0.2],\n", " [4.6, 3.2, 1.4, 0.2],\n", " [5.3, 3.7, 1.5, 0.2],\n", " [5. , 3.3, 1.4, 0.2],\n", " [7. , 3.2, 4.7, 1.4],\n", " [6.4, 3.2, 4.5, 1.5],\n", " [6.9, 3.1, 4.9, 1.5],\n", " [5.5, 2.3, 4. , 1.3],\n", " [6.5, 2.8, 4.6, 1.5],\n", " [5.7, 2.8, 4.5, 1.3],\n", " [6.3, 3.3, 4.7, 1.6],\n", " [4.9, 2.4, 3.3, 1. ],\n", " [6.6, 2.9, 4.6, 1.3],\n", " [5.2, 2.7, 3.9, 1.4],\n", " [5. , 2. , 3.5, 1. ],\n", " [5.9, 3. , 4.2, 1.5],\n", " [6. , 2.2, 4. , 1. ],\n", " [6.1, 2.9, 4.7, 1.4],\n", " [5.6, 2.9, 3.6, 1.3],\n", " [6.7, 3.1, 4.4, 1.4],\n", " [5.6, 3. , 4.5, 1.5],\n", " [5.8, 2.7, 4.1, 1. ],\n", " [6.2, 2.2, 4.5, 1.5],\n", " [5.6, 2.5, 3.9, 1.1],\n", " [5.9, 3.2, 4.8, 1.8],\n", " [6.1, 2.8, 4. , 1.3],\n", " [6.3, 2.5, 4.9, 1.5],\n", " [6.1, 2.8, 4.7, 1.2],\n", " [6.4, 2.9, 4.3, 1.3],\n", " [6.6, 3. , 4.4, 1.4],\n", " [6.8, 2.8, 4.8, 1.4],\n", " [6.7, 3. , 5. , 1.7],\n", " [6. , 2.9, 4.5, 1.5],\n", " [5.7, 2.6, 3.5, 1. ],\n", " [5.5, 2.4, 3.8, 1.1],\n", " [5.5, 2.4, 3.7, 1. ],\n", " [5.8, 2.7, 3.9, 1.2],\n", " [6. , 2.7, 5.1, 1.6],\n", " [5.4, 3. , 4.5, 1.5],\n", " [6. , 3.4, 4.5, 1.6],\n", " [6.7, 3.1, 4.7, 1.5],\n", " [6.3, 2.3, 4.4, 1.3],\n", " [5.6, 3. , 4.1, 1.3],\n", " [5.5, 2.5, 4. , 1.3],\n", " [5.5, 2.6, 4.4, 1.2],\n", " [6.1, 3. , 4.6, 1.4],\n", " [5.8, 2.6, 4. , 1.2],\n", " [5. , 2.3, 3.3, 1. ],\n", " [5.6, 2.7, 4.2, 1.3],\n", " [5.7, 3. , 4.2, 1.2],\n", " [5.7, 2.9, 4.2, 1.3],\n", " [6.2, 2.9, 4.3, 1.3],\n", " [5.1, 2.5, 3. , 1.1],\n", " [5.7, 2.8, 4.1, 1.3],\n", " [6.3, 3.3, 6. , 2.5],\n", " [5.8, 2.7, 5.1, 1.9],\n", " [7.1, 3. , 5.9, 2.1],\n", " [6.3, 2.9, 5.6, 1.8],\n", " [6.5, 3. , 5.8, 2.2],\n", " [7.6, 3. , 6.6, 2.1],\n", " [4.9, 2.5, 4.5, 1.7],\n", " [7.3, 2.9, 6.3, 1.8],\n", " [6.7, 2.5, 5.8, 1.8],\n", " [7.2, 3.6, 6.1, 2.5],\n", " [6.5, 3.2, 5.1, 2. ],\n", " [6.4, 2.7, 5.3, 1.9],\n", " [6.8, 3. , 5.5, 2.1],\n", " [5.7, 2.5, 5. , 2. ],\n", " [5.8, 2.8, 5.1, 2.4],\n", " [6.4, 3.2, 5.3, 2.3],\n", " [6.5, 3. , 5.5, 1.8],\n", " [7.7, 3.8, 6.7, 2.2],\n", " [7.7, 2.6, 6.9, 2.3],\n", " [6. , 2.2, 5. , 1.5],\n", " [6.9, 3.2, 5.7, 2.3],\n", " [5.6, 2.8, 4.9, 2. ],\n", " [7.7, 2.8, 6.7, 2. ],\n", " [6.3, 2.7, 4.9, 1.8],\n", " [6.7, 3.3, 5.7, 2.1],\n", " [7.2, 3.2, 6. , 1.8],\n", " [6.2, 2.8, 4.8, 1.8],\n", " [6.1, 3. , 4.9, 1.8],\n", " [6.4, 2.8, 5.6, 2.1],\n", " [7.2, 3. , 5.8, 1.6],\n", " [7.4, 2.8, 6.1, 1.9],\n", " [7.9, 3.8, 6.4, 2. ],\n", " [6.4, 2.8, 5.6, 2.2],\n", " [6.3, 2.8, 5.1, 1.5],\n", " [6.1, 2.6, 5.6, 1.4],\n", " [7.7, 3. , 6.1, 2.3],\n", " [6.3, 3.4, 5.6, 2.4],\n", " [6.4, 3.1, 5.5, 1.8],\n", " [6. , 3. , 4.8, 1.8],\n", " [6.9, 3.1, 5.4, 2.1],\n", " [6.7, 3.1, 5.6, 2.4],\n", " [6.9, 3.1, 5.1, 2.3],\n", " [5.8, 2.7, 5.1, 1.9],\n", " [6.8, 3.2, 5.9, 2.3],\n", " [6.7, 3.3, 5.7, 2.5],\n", " [6.7, 3. , 5.2, 2.3],\n", " [6.3, 2.5, 5. , 1.9],\n", " [6.5, 3. , 5.2, 2. ],\n", " [6.2, 3.4, 5.4, 2.3],\n", " [5.9, 3. , 5.1, 1.8]]), 'target': array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n", " 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n", " 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n", " 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n", " 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2]), 'frame': None, 'target_names': array(['setosa', 'versicolor', 'virginica'], dtype='\n" ] } ], "source": [ "print(type(X))" ] }, { "cell_type": "markdown", "id": "cbb7b02b", "metadata": {}, "source": [ "This means we are working with an object of type `Bunch`. The `Bunch` object X has the following attributes:\n", "\n", "- `data`: the data matrix\n", "- `target`: the classification target\n", "- `feature_names`: the names of the dataset columns\n", "- `target_names`: the names o the target classes\n", "\n", "To access the 2 numpy 2 arrays that contain the data matrix and the target values you use these commands\n", "\n", "1. `X_data = X[\"data\"]` or `X.data`\n", "2. `X_target = X[\"target\"]` or `X.target`\n", "\n", "The same syntax works for `feature_names` or `target_names`.\n", "\n", "You can read more about this data type at this [link](https://scikit-learn.org/stable/modules/generated/sklearn.utils.Bunch.html). Let's see this in action" ] }, { "cell_type": "code", "execution_count": null, "id": "6fb781b5", "metadata": { "scrolled": true }, "outputs": [], "source": [ "print(X)" ] }, { "cell_type": "code", "execution_count": 4, "id": "478de57b", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[5.1 3.5 1.4 0.2]\n", " [4.9 3. 1.4 0.2]\n", " [4.7 3.2 1.3 0.2]\n", " [4.6 3.1 1.5 0.2]\n", " [5. 3.6 1.4 0.2]\n", " [5.4 3.9 1.7 0.4]\n", " [4.6 3.4 1.4 0.3]\n", " [5. 3.4 1.5 0.2]\n", " [4.4 2.9 1.4 0.2]\n", " [4.9 3.1 1.5 0.1]\n", " [5.4 3.7 1.5 0.2]\n", " [4.8 3.4 1.6 0.2]\n", " [4.8 3. 1.4 0.1]\n", " [4.3 3. 1.1 0.1]\n", " [5.8 4. 1.2 0.2]\n", " [5.7 4.4 1.5 0.4]\n", " [5.4 3.9 1.3 0.4]\n", " [5.1 3.5 1.4 0.3]\n", " [5.7 3.8 1.7 0.3]\n", " [5.1 3.8 1.5 0.3]\n", " [5.4 3.4 1.7 0.2]\n", " [5.1 3.7 1.5 0.4]\n", " [4.6 3.6 1. 0.2]\n", " [5.1 3.3 1.7 0.5]\n", " [4.8 3.4 1.9 0.2]\n", " [5. 3. 1.6 0.2]\n", " [5. 3.4 1.6 0.4]\n", " [5.2 3.5 1.5 0.2]\n", " [5.2 3.4 1.4 0.2]\n", " [4.7 3.2 1.6 0.2]\n", " [4.8 3.1 1.6 0.2]\n", " [5.4 3.4 1.5 0.4]\n", " [5.2 4.1 1.5 0.1]\n", " [5.5 4.2 1.4 0.2]\n", " [4.9 3.1 1.5 0.2]\n", " [5. 3.2 1.2 0.2]\n", " [5.5 3.5 1.3 0.2]\n", " [4.9 3.6 1.4 0.1]\n", " [4.4 3. 1.3 0.2]\n", " [5.1 3.4 1.5 0.2]\n", " [5. 3.5 1.3 0.3]\n", " [4.5 2.3 1.3 0.3]\n", " [4.4 3.2 1.3 0.2]\n", " [5. 3.5 1.6 0.6]\n", " [5.1 3.8 1.9 0.4]\n", " [4.8 3. 1.4 0.3]\n", " [5.1 3.8 1.6 0.2]\n", " [4.6 3.2 1.4 0.2]\n", " [5.3 3.7 1.5 0.2]\n", " [5. 3.3 1.4 0.2]\n", " [7. 3.2 4.7 1.4]\n", " [6.4 3.2 4.5 1.5]\n", " [6.9 3.1 4.9 1.5]\n", " [5.5 2.3 4. 1.3]\n", " [6.5 2.8 4.6 1.5]\n", " [5.7 2.8 4.5 1.3]\n", " [6.3 3.3 4.7 1.6]\n", " [4.9 2.4 3.3 1. ]\n", " [6.6 2.9 4.6 1.3]\n", " [5.2 2.7 3.9 1.4]\n", " [5. 2. 3.5 1. ]\n", " [5.9 3. 4.2 1.5]\n", " [6. 2.2 4. 1. ]\n", " [6.1 2.9 4.7 1.4]\n", " [5.6 2.9 3.6 1.3]\n", " [6.7 3.1 4.4 1.4]\n", " [5.6 3. 4.5 1.5]\n", " [5.8 2.7 4.1 1. ]\n", " [6.2 2.2 4.5 1.5]\n", " [5.6 2.5 3.9 1.1]\n", " [5.9 3.2 4.8 1.8]\n", " [6.1 2.8 4. 1.3]\n", " [6.3 2.5 4.9 1.5]\n", " [6.1 2.8 4.7 1.2]\n", " [6.4 2.9 4.3 1.3]\n", " [6.6 3. 4.4 1.4]\n", " [6.8 2.8 4.8 1.4]\n", " [6.7 3. 5. 1.7]\n", " [6. 2.9 4.5 1.5]\n", " [5.7 2.6 3.5 1. ]\n", " [5.5 2.4 3.8 1.1]\n", " [5.5 2.4 3.7 1. ]\n", " [5.8 2.7 3.9 1.2]\n", " [6. 2.7 5.1 1.6]\n", " [5.4 3. 4.5 1.5]\n", " [6. 3.4 4.5 1.6]\n", " [6.7 3.1 4.7 1.5]\n", " [6.3 2.3 4.4 1.3]\n", " [5.6 3. 4.1 1.3]\n", " [5.5 2.5 4. 1.3]\n", " [5.5 2.6 4.4 1.2]\n", " [6.1 3. 4.6 1.4]\n", " [5.8 2.6 4. 1.2]\n", " [5. 2.3 3.3 1. ]\n", " [5.6 2.7 4.2 1.3]\n", " [5.7 3. 4.2 1.2]\n", " [5.7 2.9 4.2 1.3]\n", " [6.2 2.9 4.3 1.3]\n", " [5.1 2.5 3. 1.1]\n", " [5.7 2.8 4.1 1.3]\n", " [6.3 3.3 6. 2.5]\n", " [5.8 2.7 5.1 1.9]\n", " [7.1 3. 5.9 2.1]\n", " [6.3 2.9 5.6 1.8]\n", " [6.5 3. 5.8 2.2]\n", " [7.6 3. 6.6 2.1]\n", " [4.9 2.5 4.5 1.7]\n", " [7.3 2.9 6.3 1.8]\n", " [6.7 2.5 5.8 1.8]\n", " [7.2 3.6 6.1 2.5]\n", " [6.5 3.2 5.1 2. ]\n", " [6.4 2.7 5.3 1.9]\n", " [6.8 3. 5.5 2.1]\n", " [5.7 2.5 5. 2. ]\n", " [5.8 2.8 5.1 2.4]\n", " [6.4 3.2 5.3 2.3]\n", " [6.5 3. 5.5 1.8]\n", " [7.7 3.8 6.7 2.2]\n", " [7.7 2.6 6.9 2.3]\n", " [6. 2.2 5. 1.5]\n", " [6.9 3.2 5.7 2.3]\n", " [5.6 2.8 4.9 2. ]\n", " [7.7 2.8 6.7 2. ]\n", " [6.3 2.7 4.9 1.8]\n", " [6.7 3.3 5.7 2.1]\n", " [7.2 3.2 6. 1.8]\n", " [6.2 2.8 4.8 1.8]\n", " [6.1 3. 4.9 1.8]\n", " [6.4 2.8 5.6 2.1]\n", " [7.2 3. 5.8 1.6]\n", " [7.4 2.8 6.1 1.9]\n", " [7.9 3.8 6.4 2. ]\n", " [6.4 2.8 5.6 2.2]\n", " [6.3 2.8 5.1 1.5]\n", " [6.1 2.6 5.6 1.4]\n", " [7.7 3. 6.1 2.3]\n", " [6.3 3.4 5.6 2.4]\n", " [6.4 3.1 5.5 1.8]\n", " [6. 3. 4.8 1.8]\n", " [6.9 3.1 5.4 2.1]\n", " [6.7 3.1 5.6 2.4]\n", " [6.9 3.1 5.1 2.3]\n", " [5.8 2.7 5.1 1.9]\n", " [6.8 3.2 5.9 2.3]\n", " [6.7 3.3 5.7 2.5]\n", " [6.7 3. 5.2 2.3]\n", " [6.3 2.5 5. 1.9]\n", " [6.5 3. 5.2 2. ]\n", " [6.2 3.4 5.4 2.3]\n", " [5.9 3. 5.1 1.8]]\n" ] } ], "source": [ "X_data = X[\"data\"]\n", "print(X_data)" ] }, { "cell_type": "code", "execution_count": 5, "id": "3bc95ad4", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n", " 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n", " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2\n", " 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n", " 2 2]\n" ] } ], "source": [ "X_target = X[\"target\"]\n", "print(X_target)" ] }, { "cell_type": "code", "execution_count": 6, "id": "e76096d9", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "\n" ] } ], "source": [ "print(type(X_data))\n", "print(type(X_target))" ] }, { "cell_type": "markdown", "id": "c09d7c83", "metadata": {}, "source": [ "It is also possible to load the data as a Pandas dataframe. Pandas is a Python package for storing and manipulating data. In Pandas, data is stored in a Dataframe object. The dataframe object stores data in a table (rows and columns). Additionally, the dataframe object has methods to manipulate and analyze the data it contains. " ] }, { "cell_type": "code", "execution_count": 7, "id": "88669438", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'data': sepal length (cm) sepal width (cm) petal length (cm) petal width (cm)\n", "0 5.1 3.5 1.4 0.2\n", "1 4.9 3.0 1.4 0.2\n", "2 4.7 3.2 1.3 0.2\n", "3 4.6 3.1 1.5 0.2\n", "4 5.0 3.6 1.4 0.2\n", ".. ... ... ... ...\n", "145 6.7 3.0 5.2 2.3\n", "146 6.3 2.5 5.0 1.9\n", "147 6.5 3.0 5.2 2.0\n", "148 6.2 3.4 5.4 2.3\n", "149 5.9 3.0 5.1 1.8\n", "\n", "[150 rows x 4 columns], 'target': 0 0\n", "1 0\n", "2 0\n", "3 0\n", "4 0\n", " ..\n", "145 2\n", "146 2\n", "147 2\n", "148 2\n", "149 2\n", "Name: target, Length: 150, dtype: int64, 'frame': sepal length (cm) sepal width (cm) petal length (cm) petal width (cm) \\\n", "0 5.1 3.5 1.4 0.2 \n", "1 4.9 3.0 1.4 0.2 \n", "2 4.7 3.2 1.3 0.2 \n", "3 4.6 3.1 1.5 0.2 \n", "4 5.0 3.6 1.4 0.2 \n", ".. ... ... ... ... \n", "145 6.7 3.0 5.2 2.3 \n", "146 6.3 2.5 5.0 1.9 \n", "147 6.5 3.0 5.2 2.0 \n", "148 6.2 3.4 5.4 2.3 \n", "149 5.9 3.0 5.1 1.8 \n", "\n", " target \n", "0 0 \n", "1 0 \n", "2 0 \n", "3 0 \n", "4 0 \n", ".. ... \n", "145 2 \n", "146 2 \n", "147 2 \n", "148 2 \n", "149 2 \n", "\n", "[150 rows x 5 columns], 'target_names': array(['setosa', 'versicolor', 'virginica'], dtype='\n", " sepal length (cm) sepal width (cm) petal length (cm) petal width (cm)\n", "0 5.1 3.5 1.4 0.2\n", "1 4.9 3.0 1.4 0.2\n", "2 4.7 3.2 1.3 0.2\n", "3 4.6 3.1 1.5 0.2\n", "4 5.0 3.6 1.4 0.2\n" ] } ], "source": [ "Z_data = Z[\"data\"]\n", "print(type(Z_data))\n", "print(Z_data.head())" ] }, { "cell_type": "code", "execution_count": 9, "id": "0023c7f8", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "0 0\n", "1 0\n", "2 0\n", "3 0\n", "4 0\n", "Name: target, dtype: int64\n" ] } ], "source": [ "Z_target = Z[\"target\"]\n", "print(type(Z_target))\n", "print(Z_target.head())" ] }, { "cell_type": "code", "execution_count": 10, "id": "faacff2d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['setosa' 'versicolor' 'virginica']\n" ] } ], "source": [ "Z_names = Z[\"target_names\"]\n", "print(Z_names)" ] }, { "cell_type": "markdown", "id": "b2cb374d", "metadata": {}, "source": [ "## Loading other datasets\n", "\n", "In general you do not develop machine learning applications with a toy dataset. Instead your dataset comes from a database or a file (e.g., csv, Excel). Scikit-learn offers limited tools to import files. This means you have to use other tools, like Pandas to import your file into dataframes or arrays. To load a `.csv` file you can use the Pandas method `read_csv()`, see this [link](https://pandas.pydata.org/docs/reference/api/pandas.read_csv.html) for the full documentation." ] }, { "cell_type": "code", "execution_count": 11, "id": "140c2a7a", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2.0.3\n" ] } ], "source": [ "import pandas as pd\n", "print(pd.__version__)" ] }, { "cell_type": "code", "execution_count": 12, "id": "6bf71989", "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " rank discipline phd service sex salary\n", "0 Prof B 56 49 Male 186960\n", "1 Prof A 12 6 Male 93000\n", "2 Prof A 23 20 Male 110515\n", "3 Prof A 40 31 Male 131205\n", "4 Prof B 20 18 Male 104800\n" ] } ], "source": [ "df = pd.read_csv(\"datasets/Salaries.csv\")\n", "print(df.head())" ] }, { "cell_type": "markdown", "id": "4190df46", "metadata": {}, "source": [ "## Generating a dataset\n", "\n", "Scikit-learn has built in functions that allow you to create a random dataset These randomly generated datasets can then be used to explore various machine learning algorithms." ] }, { "cell_type": "code", "execution_count": 13, "id": "f2858bc7", "metadata": {}, "outputs": [], "source": [ "from sklearn.datasets import make_blobs\n", "X, y = make_blobs(n_samples=100, centers=2, n_features=2, random_state=0)" ] }, { "cell_type": "code", "execution_count": 15, "id": "a27dd649", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " \n", "(100, 2)\n" ] } ], "source": [ "print(type(X), type(y))\n", "print(X.shape)" ] }, { "cell_type": "code", "execution_count": 16, "id": "54cdc0b5", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[1 1 0 0 1 0 0 1 0 1 0 1 0 0 1 1 1 0 1 1 0 0 1 0 1 0 1 0 0 1 1 0 1 1 1 0 1\n", " 1 0 1 0 0 0 0 1 1 1 1 0 0 1 1 0 0 0 0 0 1 1 1 1 0 0 1 0 1 0 0 1 0 0 1 1 0\n", " 0 0 1 1 0 0 1 0 0 0 0 0 1 0 1 1 1 1 1 1 0 0 1 1 0 1]\n" ] } ], "source": [ "print(y)" ] }, { "cell_type": "markdown", "id": "b5b9f603", "metadata": {}, "source": [ "We can plot the data that we just created using the [matplotlib](https://matplotlib.org/). " ] }, { "cell_type": "code", "execution_count": 17, "id": "7697c3e1", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "colors = {0:'red', 1:'blue'};\n", "c_arr=[colors[k] for k in y]\n", "plt.scatter(X[:, 0], X[:, 1], marker=\"o\", c=c_arr, s=50, edgecolor=\"k\");" ] }, { "cell_type": "markdown", "id": "3da0c926", "metadata": {}, "source": [ "## Real world data sets\n", "\n", "Using scikit-learn you can also import real world datasets. The real world datasets are larger than the toy datasets." ] }, { "cell_type": "code", "execution_count": 18, "id": "5610cc26", "metadata": {}, "outputs": [], "source": [ "from sklearn.datasets import fetch_california_housing\n", "RW = fetch_california_housing(as_frame=True)" ] }, { "cell_type": "code", "execution_count": 19, "id": "518ce405", "metadata": {}, "outputs": [], "source": [ "RW_data = RW[\"data\"]\n", "RW_target = RW[\"target\"]" ] }, { "cell_type": "code", "execution_count": 20, "id": "f91787ff", "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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MedIncHouseAgeAveRoomsAveBedrmsPopulationAveOccupLatitudeLongitude
08.325241.06.9841271.023810322.02.55555637.88-122.23
18.301421.06.2381370.9718802401.02.10984237.86-122.22
27.257452.08.2881361.073446496.02.80226037.85-122.24
35.643152.05.8173521.073059558.02.54794537.85-122.25
43.846252.06.2818531.081081565.02.18146737.85-122.25
\n", "
" ], "text/plain": [ " MedInc HouseAge AveRooms AveBedrms Population AveOccup Latitude \\\n", "0 8.3252 41.0 6.984127 1.023810 322.0 2.555556 37.88 \n", "1 8.3014 21.0 6.238137 0.971880 2401.0 2.109842 37.86 \n", "2 7.2574 52.0 8.288136 1.073446 496.0 2.802260 37.85 \n", "3 5.6431 52.0 5.817352 1.073059 558.0 2.547945 37.85 \n", "4 3.8462 52.0 6.281853 1.081081 565.0 2.181467 37.85 \n", "\n", " Longitude \n", "0 -122.23 \n", "1 -122.22 \n", "2 -122.24 \n", "3 -122.25 \n", "4 -122.25 " ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "RW_data.head()" ] }, { "cell_type": "code", "execution_count": 21, "id": "994fe56c", "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "0 4.526\n", "1 3.585\n", "2 3.521\n", "3 3.413\n", "4 3.422\n", "Name: MedHouseVal, dtype: float64" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "RW_target.head()" ] }, { "cell_type": "code", "execution_count": 22, "id": "c5e06b81", "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "'.. _california_housing_dataset:\\n\\nCalifornia Housing dataset\\n--------------------------\\n\\n**Data Set Characteristics:**\\n\\n :Number of Instances: 20640\\n\\n :Number of Attributes: 8 numeric, predictive attributes and the target\\n\\n :Attribute Information:\\n - MedInc median income in block group\\n - HouseAge median house age in block group\\n - AveRooms average number of rooms per household\\n - AveBedrms average number of bedrooms per household\\n - Population block group population\\n - AveOccup average number of household members\\n - Latitude block group latitude\\n - Longitude block group longitude\\n\\n :Missing Attribute Values: None\\n\\nThis dataset was obtained from the StatLib repository.\\nhttps://www.dcc.fc.up.pt/~ltorgo/Regression/cal_housing.html\\n\\nThe target variable is the median house value for California districts,\\nexpressed in hundreds of thousands of dollars ($100,000).\\n\\nThis dataset was derived from the 1990 U.S. census, using one row per census\\nblock group. A block group is the smallest geographical unit for which the U.S.\\nCensus Bureau publishes sample data (a block group typically has a population\\nof 600 to 3,000 people).\\n\\nA household is a group of people residing within a home. Since the average\\nnumber of rooms and bedrooms in this dataset are provided per household, these\\ncolumns may take surprisingly large values for block groups with few households\\nand many empty houses, such as vacation resorts.\\n\\nIt can be downloaded/loaded using the\\n:func:`sklearn.datasets.fetch_california_housing` function.\\n\\n.. topic:: References\\n\\n - Pace, R. Kelley and Ronald Barry, Sparse Spatial Autoregressions,\\n Statistics and Probability Letters, 33 (1997) 291-297\\n'" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "RW.DESCR" ] }, { "cell_type": "markdown", "id": "68fe50c1", "metadata": {}, "source": [ "## Exploratory data analysis\n", "\n", "It is important to explore and understand your dataset prior to applying machine learning algorithms to it. There are a few functions in Pandas that are helpful for this. \n", "\n", "We will explore these functions using the iris dataset first. We will perform a few transformations on this dataset prior to the analysis." ] }, { "cell_type": "code", "execution_count": 24, "id": "109fd0f1", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " sepal length (cm) sepal width (cm) petal length (cm) petal width (cm) \\\n", "0 5.1 3.5 1.4 0.2 \n", "1 4.9 3.0 1.4 0.2 \n", "2 4.7 3.2 1.3 0.2 \n", "3 4.6 3.1 1.5 0.2 \n", "4 5.0 3.6 1.4 0.2 \n", "5 5.4 3.9 1.7 0.4 \n", "6 4.6 3.4 1.4 0.3 \n", "7 5.0 3.4 1.5 0.2 \n", "8 4.4 2.9 1.4 0.2 \n", "9 4.9 3.1 1.5 0.1 \n", "\n", " target target_names \n", "0 0 setosa \n", "1 0 setosa \n", "2 0 setosa \n", "3 0 setosa \n", "4 0 setosa \n", "5 0 setosa \n", "6 0 setosa \n", "7 0 setosa \n", "8 0 setosa \n", "9 0 setosa \n" ] } ], "source": [ "## Data manipulation\n", "Z_df = Z.frame\n", "\n", "Z_df[\"target_names\"] =Z_df[\"target\"].replace(to_replace=\n", " {0: Z.target_names[0], \n", " 1: Z.target_names[1], \n", " 2: Z.target_names[2]})\n", "print(Z_df.head(10))" ] }, { "cell_type": "code", "execution_count": 25, "id": "88e53ebd", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " sepal length (cm) sepal width (cm) petal length (cm) petal width (cm) \\\n", "145 6.7 3.0 5.2 2.3 \n", "146 6.3 2.5 5.0 1.9 \n", "147 6.5 3.0 5.2 2.0 \n", "148 6.2 3.4 5.4 2.3 \n", "149 5.9 3.0 5.1 1.8 \n", "\n", " target target_names \n", "145 2 virginica \n", "146 2 virginica \n", "147 2 virginica \n", "148 2 virginica \n", "149 2 virginica \n" ] } ], "source": [ "print(Z_df.tail())" ] }, { "cell_type": "code", "execution_count": 26, "id": "c8e00900", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 150 entries, 0 to 149\n", "Data columns (total 6 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 sepal length (cm) 150 non-null float64\n", " 1 sepal width (cm) 150 non-null float64\n", " 2 petal length (cm) 150 non-null float64\n", " 3 petal width (cm) 150 non-null float64\n", " 4 target 150 non-null int64 \n", " 5 target_names 150 non-null object \n", "dtypes: float64(4), int64(1), object(1)\n", "memory usage: 7.2+ KB\n" ] } ], "source": [ "## Pandas info\n", "Z_df.info()" ] }, { "cell_type": "code", "execution_count": 27, "id": "7f8571bd", "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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sepal length (cm)sepal width (cm)petal length (cm)petal width (cm)target
count150.000000150.000000150.000000150.000000150.000000
mean5.8433333.0573333.7580001.1993331.000000
std0.8280660.4358661.7652980.7622380.819232
min4.3000002.0000001.0000000.1000000.000000
25%5.1000002.8000001.6000000.3000000.000000
50%5.8000003.0000004.3500001.3000001.000000
75%6.4000003.3000005.1000001.8000002.000000
max7.9000004.4000006.9000002.5000002.000000
\n", "
" ], "text/plain": [ " sepal length (cm) sepal width (cm) petal length (cm) \\\n", "count 150.000000 150.000000 150.000000 \n", "mean 5.843333 3.057333 3.758000 \n", "std 0.828066 0.435866 1.765298 \n", "min 4.300000 2.000000 1.000000 \n", "25% 5.100000 2.800000 1.600000 \n", "50% 5.800000 3.000000 4.350000 \n", "75% 6.400000 3.300000 5.100000 \n", "max 7.900000 4.400000 6.900000 \n", "\n", " petal width (cm) target \n", "count 150.000000 150.000000 \n", "mean 1.199333 1.000000 \n", "std 0.762238 0.819232 \n", "min 0.100000 0.000000 \n", "25% 0.300000 0.000000 \n", "50% 1.300000 1.000000 \n", "75% 1.800000 2.000000 \n", "max 2.500000 2.000000 " ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "## Pandas describe\n", "Z_df.describe()" ] }, { "cell_type": "markdown", "id": "0c1600de", "metadata": {}, "source": [ "It is also very helpful to visualize variables of interest. We will use a visualization package called [Seaborn](https://seaborn.pydata.org/). Seaborn is intended for visualizing statistical data. In particular, most functions require as input a dataframe." ] }, { "cell_type": "code", "execution_count": 28, "id": "421e53a8", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.12.2\n" ] } ], "source": [ "## Seaborn to visualize data\n", "import seaborn as sns\n", "print(sns.__version__)" ] }, { "cell_type": "code", "execution_count": 29, "id": "3a28d951", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "## Boxplot\n", "sns.boxplot(data=Z_df, x=\"target_names\", y=\"sepal length (cm)\");" ] }, { "cell_type": "code", "execution_count": 30, "id": "2588daa0", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/share/pkg.8/python3/3.10.12/install/lib/python3.10/site-packages/seaborn/axisgrid.py:118: UserWarning: The figure layout has changed to tight\n", " self._figure.tight_layout(*args, **kwargs)\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "## Pairplot\n", "sns.pairplot(Z_df.drop(\"target\", axis=1), hue=\"target_names\");" ] }, { "cell_type": "markdown", "id": "27a62862", "metadata": {}, "source": [ "## Exercises\n", "Let's do some exploratory data analysis on the RW_data set." ] }, { "cell_type": "code", "execution_count": 31, "id": "018c9403", "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 20640 entries, 0 to 20639\n", "Data columns (total 8 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 MedInc 20640 non-null float64\n", " 1 HouseAge 20640 non-null float64\n", " 2 AveRooms 20640 non-null float64\n", " 3 AveBedrms 20640 non-null float64\n", " 4 Population 20640 non-null float64\n", " 5 AveOccup 20640 non-null float64\n", " 6 Latitude 20640 non-null float64\n", " 7 Longitude 20640 non-null float64\n", "dtypes: float64(8)\n", "memory usage: 1.3 MB\n" ] } ], "source": [ "### Determine if there are any null values in the RW_data dataframe ###\n", "RW_data.info()" ] }, { "cell_type": "code", "execution_count": 32, "id": "05b91219", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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MedIncHouseAgeAveRoomsAveBedrmsPopulationAveOccupLatitudeLongitude
count20640.00000020640.00000020640.00000020640.00000020640.00000020640.00000020640.00000020640.000000
mean3.87067128.6394865.4290001.0966751425.4767443.07065535.631861-119.569704
std1.89982212.5855582.4741730.4739111132.46212210.3860502.1359522.003532
min0.4999001.0000000.8461540.3333333.0000000.69230832.540000-124.350000
25%2.56340018.0000004.4407161.006079787.0000002.42974133.930000-121.800000
50%3.53480029.0000005.2291291.0487801166.0000002.81811634.260000-118.490000
75%4.74325037.0000006.0523811.0995261725.0000003.28226137.710000-118.010000
max15.00010052.000000141.90909134.06666735682.0000001243.33333341.950000-114.310000
\n", "
" ], "text/plain": [ " MedInc HouseAge AveRooms AveBedrms Population \\\n", "count 20640.000000 20640.000000 20640.000000 20640.000000 20640.000000 \n", "mean 3.870671 28.639486 5.429000 1.096675 1425.476744 \n", "std 1.899822 12.585558 2.474173 0.473911 1132.462122 \n", "min 0.499900 1.000000 0.846154 0.333333 3.000000 \n", "25% 2.563400 18.000000 4.440716 1.006079 787.000000 \n", "50% 3.534800 29.000000 5.229129 1.048780 1166.000000 \n", "75% 4.743250 37.000000 6.052381 1.099526 1725.000000 \n", "max 15.000100 52.000000 141.909091 34.066667 35682.000000 \n", "\n", " AveOccup Latitude Longitude \n", "count 20640.000000 20640.000000 20640.000000 \n", "mean 3.070655 35.631861 -119.569704 \n", "std 10.386050 2.135952 2.003532 \n", "min 0.692308 32.540000 -124.350000 \n", "25% 2.429741 33.930000 -121.800000 \n", "50% 2.818116 34.260000 -118.490000 \n", "75% 3.282261 37.710000 -118.010000 \n", "max 1243.333333 41.950000 -114.310000 " ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "### Compute the descriptive statistics of all the input features ###\n", "RW_data.describe()" ] }, { "cell_type": "code", "execution_count": 33, "id": "248a02cc", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "### Create a horizontal box plot RW_DATA\n", "### What is an important observation from this plot?\n", "### How is it a useful visualzation? How is it not a useful visualization?\n", "sns.boxplot(data=RW_data, orient=\"h\");" ] }, { "cell_type": "markdown", "id": "6d3c48d4", "metadata": {}, "source": [ "## Dataset summary\n", "\n", "We have 4 datasets stored in our notebook which we summarize below\n", "\n", "- Iris dataset (toy dataset)\n", "- Generated dataset \n", "- California housing dataset (real world dataset)\n", "- Salaries dataset (toy dataset)\n", "\n", "\n", "We will used these datasets in subsequent cells of the notebook when we explore more techniques in Scikit-learn." ] }, { "cell_type": "markdown", "id": "ef0781d8", "metadata": {}, "source": [ "## Test train split\n", "\n", "In order to train and test your model you need to split your dataset into two sets:\n", "\n", "- training set\n", "- test set\n", "\n", "This is easy to accomplish with `sklearn.model_selection.train_test_split`.\n", "\n", "We will see how this function works using our generated dataset. This is because it is small and easy to confirm the expected behavior." ] }, { "cell_type": "code", "execution_count": 34, "id": "69b11f2b", "metadata": {}, "outputs": [], "source": [ "from sklearn.model_selection import train_test_split\n", "\n", "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.20, random_state=42)" ] }, { "cell_type": "code", "execution_count": 35, "id": "7f6f4fc4", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Shape of X_train: (80, 2) , Shape of X_test: (20, 2)\n", "Shape of y_train: (80,) , Shape of y_test: (20,)\n" ] } ], "source": [ "print(\"Shape of X_train: \", X_train.shape, \", Shape of X_test: \", X_test.shape)\n", "print(\"Shape of y_train: \", y_train.shape, \", Shape of y_test: \", y_test.shape)" ] }, { "cell_type": "markdown", "id": "a411da82", "metadata": {}, "source": [ "## Scaling data\n", "\n", "We have now observed and explored a few different datasets. One important observation we made was that our datasets can have very different scales.\n", "\n", "Why is it not a good idea to run a machine learning algorithm on a dataset where the input features have scales that differ by orders of magnitude?\n", "\n", "What can we do to fix this? As the title of this section suggests, we will scale our data. This is a way to ensure that the numerical features of our datasets have scales that are of the same order of magnitude.\n", "\n", "Here are a few common ways to scale data:\n", "\n", " - Standard scaling\n", " - Min-Max scaling\n", " \n", "These (and others) are all implemented in scikit-learn. The methodology for using a scaling technique in scikit-learn is similar. You will always start by creating a scaler object and then use this object to scale your data." ] }, { "cell_type": "markdown", "id": "e9017186", "metadata": {}, "source": [ "### Standard Scaling\n", "Standard scaling scales data so that all the numerical features have zero mean and unit variance.\n", "\n", "Since the scales of the RW dataset were very different, we will apply the scaler to this dataset and then replot the box and whisker plot." ] }, { "cell_type": "code", "execution_count": 39, "id": "9a1418ad", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[ 2.34476576 0.98214266 0.62855945 ... -0.04959654 1.05254828\n", " -1.32783522]\n", " [ 2.33223796 -0.60701891 0.32704136 ... -0.09251223 1.04318455\n", " -1.32284391]\n", " [ 1.7826994 1.85618152 1.15562047 ... -0.02584253 1.03850269\n", " -1.33282653]\n", " ...\n", " [-1.14259331 -0.92485123 -0.09031802 ... -0.0717345 1.77823747\n", " -0.8237132 ]\n", " [-1.05458292 -0.84539315 -0.04021111 ... -0.09122515 1.77823747\n", " -0.87362627]\n", " [-0.78012947 -1.00430931 -0.07044252 ... -0.04368215 1.75014627\n", " -0.83369581]]\n" ] } ], "source": [ "from sklearn.preprocessing import StandardScaler\n", "scaler = StandardScaler()\n", "RW_standard = scaler.fit_transform(RW_data)\n", "print(RW_standard)" ] }, { "cell_type": "code", "execution_count": 40, "id": "9d1f20d1", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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02.3447660.9821430.628559-0.153758-0.974429-0.0495971.052548-1.327835
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" ], "text/plain": [ " MedInc HouseAge AveRooms AveBedrms Population AveOccup Latitude \\\n", "0 2.344766 0.982143 0.628559 -0.153758 -0.974429 -0.049597 1.052548 \n", "1 2.332238 -0.607019 0.327041 -0.263336 0.861439 -0.092512 1.043185 \n", "2 1.782699 1.856182 1.155620 -0.049016 -0.820777 -0.025843 1.038503 \n", "3 0.932968 1.856182 0.156966 -0.049833 -0.766028 -0.050329 1.038503 \n", "4 -0.012881 1.856182 0.344711 -0.032906 -0.759847 -0.085616 1.038503 \n", "\n", " Longitude \n", "0 -1.327835 \n", "1 -1.322844 \n", "2 -1.332827 \n", "3 -1.337818 \n", "4 -1.337818 " ] }, "execution_count": 40, "metadata": {}, "output_type": "execute_result" } ], "source": [ "RW_standard_df = pd.DataFrame(RW_standard, columns=RW_data.columns)\n", "RW_standard_df.head()" ] }, { "cell_type": "code", "execution_count": 38, "id": "e1b1232a", "metadata": { "scrolled": false }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.boxplot(data=RW_standard_df, orient=\"h\");" ] }, { "cell_type": "markdown", "id": "98eec37e", "metadata": {}, "source": [ "### Min-max scaling\n", "\n", "We can also do min-max scaling which puts everything in a range between 0 and 1." ] }, { "cell_type": "code", "execution_count": 41, "id": "8cfe9640", "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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MedIncHouseAgeAveRoomsAveBedrmsPopulationAveOccupLatitudeLongitude
00.5396680.7843140.0435120.0204690.0089410.0014990.5674810.211155
10.5380270.3921570.0382240.0189290.0672100.0011410.5653560.212151
20.4660281.0000000.0527560.0219400.0138180.0016980.5642930.210159
30.3546991.0000000.0352410.0219290.0155550.0014930.5642930.209163
40.2307761.0000000.0385340.0221660.0157520.0011980.5642930.209163
\n", "
" ], "text/plain": [ " MedInc HouseAge AveRooms AveBedrms Population AveOccup Latitude \\\n", "0 0.539668 0.784314 0.043512 0.020469 0.008941 0.001499 0.567481 \n", "1 0.538027 0.392157 0.038224 0.018929 0.067210 0.001141 0.565356 \n", "2 0.466028 1.000000 0.052756 0.021940 0.013818 0.001698 0.564293 \n", "3 0.354699 1.000000 0.035241 0.021929 0.015555 0.001493 0.564293 \n", "4 0.230776 1.000000 0.038534 0.022166 0.015752 0.001198 0.564293 \n", "\n", " Longitude \n", "0 0.211155 \n", "1 0.212151 \n", "2 0.210159 \n", "3 0.209163 \n", "4 0.209163 " ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn.preprocessing import MinMaxScaler\n", "mscaler = MinMaxScaler()\n", "RW_minmax = mscaler.fit_transform(RW_data)\n", "RW_minmax_df = pd.DataFrame(RW_minmax, columns=RW_data.columns)\n", "RW_minmax_df.head()" ] }, { "cell_type": "code", "execution_count": 42, "id": "257a6696", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.boxplot(data=RW_minmax_df, orient=\"h\");" ] }, { "cell_type": "markdown", "id": "0532e6b3", "metadata": {}, "source": [ "## Supervised learning\n", "\n", "In this section we will cover supervised learning algorithms in Scikit-Learn. Supervised learning is a machine learning technique where we train a model using *labeled* data. This trained model can then be used to predict values on new data.\n", "\n", "There are two broad categories of supervised learning:\n", "\n", "- Regression, when the model predicts continuous variables\n", "- Classification, when the model segments data into classes\n", "\n", "Scikit-learn has a standardized API which makes it easy to train different models with very similar pieces of code. Generally you will create an object for the model that you want, e.g., `LinearRegression`or `LogisticRegression`. These objects have all the methods you need to train your model and then predict values on your model.\n", "\n", "We will cover the following supervised learning methods:\n", "\n", "- Linear regression (regression)\n", "- Logistic regression (classification)" ] }, { "cell_type": "markdown", "id": "775e1932", "metadata": {}, "source": [ "### Notation\n", "We introduce notation and the general ideas behind \n", "\n", "- A pair $(x^{(i)}, y^{(i)})$ is called a training example\n", "- A set $\\{(x^{(i)}, y^{(i)})\\}_{i=1}^{m}$ is called a training set\n", "- The goal is to find a function $h(x)$ that is good at predicting targets $y$\n", "- Assume $\\hat{y} = h_{w}(x)$ depends on a parameter $w$ (or parameters $w_{i}$ if $x$ is a vector)\n", "- Use the labeled training set to *learn* the parameter(s) $w$ for the function $h_{w}(x)$\n", "- The fully trained $h_{w}(x)$ is referred to as a *model*" ] }, { "cell_type": "markdown", "id": "6ed35ae1", "metadata": {}, "source": [ "## Linear regression\n", "\n", "To create a linear regression model in scikit-learn you will instantiate the [LinearRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LinearRegression.html) object.\n", "\n", "We use the scaled Calfornia housing dataset to demonstrate how to create this object, train the model, and then predict on the test set." ] }, { "cell_type": "code", "execution_count": 43, "id": "993f83a3", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The R^2 score is : 0.60858426002245\n", "Mean squared error: 0.5159703765453236\n" ] } ], "source": [ "from sklearn.linear_model import LinearRegression\n", "from sklearn.model_selection import train_test_split\n", "from sklearn.datasets import fetch_california_housing\n", "from sklearn.preprocessing import StandardScaler\n", "from sklearn.metrics import mean_squared_error\n", "\n", "# Fetch data\n", "RW = fetch_california_housing()\n", "X = RW[\"data\"]\n", "y = RW[\"target\"]\n", "\n", "# Split\n", "X_train, X_test, y_train, y_test = train_test_split(X, y)\n", "\n", "# Standardize\n", "scaler = StandardScaler()\n", "X_train = scaler.fit_transform(X_train)\n", "X_test = scaler.fit_transform(X_test)\n", "\n", "# Create regression model\n", "reg = LinearRegression()\n", "# Train\n", "reg.fit(X_train, y_train)\n", "\n", "# Predict on test set\n", "y_pred = reg.predict(X_test)\n", "\n", "# R^2 value\n", "r2 = reg.score(X_test, y_test)\n", "print(\"The R^2 score is : \", r2)\n", "\n", "# Report Mean Square Error (mse)\n", "mse = mean_squared_error(y_test, y_pred)\n", "print(\"Mean squared error: \", mse)" ] }, { "cell_type": "code", "execution_count": 46, "id": "7e195848", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " precision recall f1-score support\n", "\n", " setosa 1.00 1.00 1.00 16\n", " versicolor 1.00 0.89 0.94 18\n", " virginica 0.85 1.00 0.92 11\n", "\n", " accuracy 0.96 45\n", " macro avg 0.95 0.96 0.95 45\n", "weighted avg 0.96 0.96 0.96 45\n", "\n" ] } ], "source": [ "## Logistic Regression\n", "\n", "from sklearn.linear_model import LogisticRegression\n", "from sklearn.model_selection import train_test_split\n", "from sklearn.datasets import load_iris\n", "from sklearn.preprocessing import StandardScaler\n", "from sklearn.metrics import classification_report\n", "\n", "# Fetch data\n", "Iris = load_iris()\n", "X = Iris[\"data\"]\n", "y = Iris[\"target\"]\n", "\n", "# Split\n", "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.30, random_state=0)\n", "\n", "# Standardize\n", "scaler = StandardScaler()\n", "X_train = scaler.fit_transform(X_train)\n", "X_test = scaler.fit_transform(X_test)\n", "\n", "# Create regression model\n", "reg = LogisticRegression()\n", "# Train\n", "reg.fit(X_train, y_train)\n", "\n", "# Predict on test set\n", "y_pred = reg.predict(X_test)\n", "\n", "\n", "# Classification report\n", "print(classification_report(y_test, y_pred, target_names=Iris.target_names))" ] }, { "cell_type": "markdown", "id": "85906013", "metadata": {}, "source": [ "## Unsupervised learning\n", "\n", "In this section we will cover unsupervised learning algorithms in Scikit-Learn. Unsupervised learning is a machine learning technique where we train a model using *un-labeled* data. With unsupervised learning algorithms you are extracting information from the data itself without any labels.\n", "\n", "Somes examples of unsupervised learning techniques that we cover are:\n", "\n", "- Clustering\n", "- Principal Component Analysis (PCA)" ] }, { "cell_type": "markdown", "id": "e9b6d5f1", "metadata": {}, "source": [ "## Clustering\n", "\n", "Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters).\n", "\n", "Here we will consider K-means clustering, where we will cluster objects into k-clusters. The clusters will be formed by determimning centroids of each cluster, then membership to the cluster is determined by an observations shortest distance to the centroid.\n", "\n", "For this problem we will work with a generated dataset." ] }, { "cell_type": "code", "execution_count": 53, "id": "ababcd6d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Cluster centers: [[ 2.64553037 5.00672164]\n", " [ 2.72491832 -7.60866643]]\n" ] } ], "source": [ "from sklearn.datasets import make_blobs\n", "from sklearn.model_selection import train_test_split\n", "from sklearn.cluster import KMeans\n", "\n", "# Generate data with 2 clusters\n", "X, y = make_blobs(n_samples=500, centers=3, n_features=2, random_state=10)\n", "\n", "# Create bcluster object\n", "cluster = KMeans(n_clusters=2, n_init=\"auto\");\n", "\n", "# Train cluster model\n", "cluster.fit(X);\n", "\n", "print(\"Cluster centers: \", cluster.cluster_centers_)" ] }, { "cell_type": "code", "execution_count": 55, "id": "32024a97", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "colors = {0:'red', 1:'blue', 2:'green'};\n", "c_arr=[colors[k] for k in y]\n", "plt.scatter(X[:, 0], X[:, 1], marker=\"o\", c=c_arr, s=25, edgecolor=\"k\");\n", "plt.scatter(cluster.cluster_centers_[:, 0], cluster.cluster_centers_[:, 1], marker='*', s=100, c='y');" ] }, { "cell_type": "markdown", "id": "3b4bfe38", "metadata": {}, "source": [ "## Principal component analysis (PCA)\n", "\n", "PCA is an unsupervised machine learning algorithm that helps to reduse the dimension of your data. The dimension of your data is the number of input features. This algorithm finds a reduced set of input features in the data that account for the majority of the variance in the data. This means that you can work with a smaller set of input features (smaller data), but you are not losing the important information from the full set of input features." ] }, { "cell_type": "code", "execution_count": 56, "id": "8fc97084", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Feature names: ['sepal length (cm)', 'sepal width (cm)', 'petal length (cm)', 'petal width (cm)']\n" ] } ], "source": [ "from sklearn.datasets import load_iris\n", "from sklearn.decomposition import PCA\n", "#from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", "\n", "iris = load_iris()\n", "print(\"Feature names: \", iris.feature_names)" ] }, { "cell_type": "code", "execution_count": 59, "id": "0ad9f98d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Shape of X: (150, 4) Shape of X_r: (150, 2)\n" ] } ], "source": [ "X = iris.data\n", "y = iris.target\n", "target_names = iris.target_names\n", "\n", "pca = PCA(n_components=2)\n", "#\n", "X_r = pca.fit_transform(X)\n", "print(\"Shape of X: \", X.shape, \"Shape of X_r: \", X_r.shape)" ] }, { "cell_type": "code", "execution_count": 60, "id": "e2ed33ac", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure()\n", "colors = [\"navy\", \"turquoise\", \"darkorange\"]\n", "lw = 2\n", "\n", "for color, i, target_name in zip(colors, [0, 1, 2], target_names):\n", " plt.scatter(\n", " X_r[y == i, 0], X_r[y == i, 1], color=color, alpha=0.8, lw=lw, label=target_name\n", " )\n", "plt.legend(loc=\"best\", shadow=False, scatterpoints=1)\n", "plt.xlabel(\"PC 1\")\n", "plt.ylabel(\"PC 2\")\n", "plt.title(\"PCA of IRIS dataset\");" ] }, { "cell_type": "markdown", "id": "49000878", "metadata": {}, "source": [ "## Summary\n", "\n", "We have covered many topics in this tutorial. We have seen how to preprocess data and train supervised and unsupervised machine learning. We can also compute simple metrics tos evaluate the performance of these models. Hopefully this has given you a better idea of how to use sklearn.\n", "\n", "\n", "Remember that the main framework for working with sklearn has the following structure:\n", "\n", "1. Import the sklearn objects you need for the code.\n", "2. Prepare a set of preprocessed (namely cleaned and scaled) data to give your model (usually in the form of numpy arrays).\n", "3. Create the model object in your code.\n", "4. Use the model object to train your model using the appropriate training method (usually `fit()`).\n", "5. Apply the model to data that the model has not seen (test data) using the appropriate prediction/transformation method (usually `predict()`).\n", "\n", "This structure and knowing the methods within the various data and model classes that accomplish this are all you need in order to work with sklearn." ] }, { "cell_type": "markdown", "id": "d347f330", "metadata": {}, "source": [ "## Exercises" ] }, { "cell_type": "code", "execution_count": null, "id": "cbda895b", "metadata": {}, "outputs": [], "source": [ "## Exercise 1 ##\n", "# Using the Calfornia housing dataset:\n", "# Train a regression model only on the first four features MedInc HouseAge AveRooms AveBedrms\n", "# Evaluate the performance of this model using MSE\n", "# Does this reduced set of features give better performance than the full set of input features?" ] }, { "cell_type": "code", "execution_count": null, "id": "dec21cc1", "metadata": {}, "outputs": [], "source": [ "## Exercise 2 ##\n", "# Load the breast cancer dataset\n", "# Create and train a random forest model on this dataset, call this object model1\n", "# Crete and train a logistic regression model on this dataset, call this object model2\n", "# Evaluate the performance of both models\n", "# Which model is more accurate?\n", "# Which model is a better choice for this application and why?" ] }, { "cell_type": "code", "execution_count": null, "id": "f915d1cc", "metadata": {}, "outputs": [], "source": [ "## Exercise 3 ##\n", "# Generate a dataset with 4 blobs using these paramenters\n", "# Perform K-means clustering to cluster the 4 blobs using these parameters\n", "# Evaluate the model using the function score()\n", "# Try to get more than 90% accuracy on the model" ] }, { "cell_type": "markdown", "id": "82e5714c", "metadata": {}, "source": [ "Tutorial evaluation at rcs.bu.edu/eval" ] }, { "cell_type": "code", "execution_count": null, "id": "f6145992", "metadata": {}, "outputs": [], "source": [ "Scott Ladenheim\n", "saladenh@bu.edu\n", "\n", "help@rcs.bu.edu" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.12" } }, "nbformat": 4, "nbformat_minor": 5 }