diff --git a/Notes/Semester 4/MLDM - Machine Learning and Data Mining/PreClassReading/MLDM_FS23_L03_Linear_Regression_PRE_CLASS_ASSIGNMENT.ipynb b/Notes/Semester 4/MLDM - Machine Learning and Data Mining/PreClassReading/MLDM_FS23_L03_Linear_Regression_PRE_CLASS_ASSIGNMENT.ipynb new file mode 100644 index 0000000..9505c13 --- /dev/null +++ b/Notes/Semester 4/MLDM - Machine Learning and Data Mining/PreClassReading/MLDM_FS23_L03_Linear_Regression_PRE_CLASS_ASSIGNMENT.ipynb @@ -0,0 +1,262 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "skYsk1dTaZ83" + }, + "source": [ + "# L03 - Linear Regression\n", + "In this lecture you will learn about **Linear Regression**. The main idea of Linear Regression is as follows: given a set of samples, where each consists of an input value x and an output value y, find a model that allows for new samples to predict their corresponding output value. For instance, assume we know for some houses their size and their prices. Then we want to \"learn\" a good estimate of the price for any house based only on its size.\n", + "\n", + "\n", + "**Organization**\n", + "\n", + "For the introduction to Linear Regression, we are using the excellent video recordings by Andrew Ng from his Coursera Course on Machine Learning. Each video is 5-10 minutes.\n", + "\n", + "If you know Linear Regression already, e.g. from previous lectures, you can just skim through the videos and read the subsequent notes for a recap and for familiarising yourself with the notation we will be using.\n", + "\n", + "At the end of this document you find some additional remarks and hints that are not covered in the videos." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "x7O9eioO74Dv" + }, + "source": [ + "# Linear Regression with One Variable\n", + "\n", + "\n", + "\n", + "* Video 1: https://www.youtube.com/watch?v=kHwlB_j7Hkc&list=PLLssT5z_DsK-h9vYZkQkYNWcItqhlRJLN&index=4\n", + "* Video 2: https://www.youtube.com/watch?v=yuH4iRcggMw&list=PLLssT5z_DsK-h9vYZkQkYNWcItqhlRJLN&index=5\n", + "* Video 3: https://www.youtube.com/watch?v=yR2ipCoFvNo&list=PLLssT5z_DsK-h9vYZkQkYNWcItqhlRJLN&index=6\n", + "* Video 4: https://www.youtube.com/watch?v=0kns1gXLYg4&list=PLLssT5z_DsK-h9vYZkQkYNWcItqhlRJLN&index=7\n", + "* Video 5: https://www.youtube.com/watch?v=F6GSRDoB-Cg&list=PLLssT5z_DsK-h9vYZkQkYNWcItqhlRJLN&index=8\n", + "* Video 6: https://www.youtube.com/watch?v=YovTqTY-PYY&list=PLLssT5z_DsK-h9vYZkQkYNWcItqhlRJLN&index=9\n", + "* Video 7: https://www.youtube.com/watch?v=GtSf2T6Co80&list=PLLssT5z_DsK-h9vYZkQkYNWcItqhlRJLN&index=10\n", + "\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "hSRYYs2z96EL" + }, + "source": [ + "# Main Concepts for Linear Regression with One Variable\n", + "\n", + "**Definition:** *Linear Regression with One Variable*\n", + "\n", + "Given a set of $m$ training samples $(x^{(i)}, y^{(i)})$, where each sample (indicated by superscript $^{(i)}$) consists of $x^{(i)}$, the input variable (or feature), and $y^{(i)}$, the output value of the sample. We define the **Hypothesis** $h$ as a linear function with two parameters $\\Theta_0$ and $\\Theta_1$: $h_\\Theta(x) = \\Theta_0 + \\Theta_1 * x$\n", + "\n", + "Our goal in Linear Regression is to find values for $\\Theta_0$ and $\\Theta_1$ such that $h_\\Theta(x^{(i)})$ is close to $y^{(i)}$ for each sample $(x^{(i)},y^{(i)})$.\n", + "\n", + "\n", + "Normally, we will use the shorthand $h(x)$ instead of $h_\\Theta(x)$ if $\\Theta$ is clear from the context.\n", + "\n", + "**Definition:** *Cost Function*\n", + "\n", + "$J(\\Theta_0, \\Theta_1) = \\frac{1}{2m} \\sum_{i=1}^m (h_\\Theta(x^{(i)}) - y^{(i)})^2$\n", + "\n", + "This is also known as the *Squared Error Function* or *Mean Squared Error (MSE) Loss*. The goal in Linear Regression is to find values for parameters $\\Theta_0$ and $\\Theta_1$ that minimize the cost function J.\n", + "\n", + "We can plot the cost function $J$ for different values of $\\Theta_0$ and $\\Theta_1$ in 3-d:\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "eoiD78kYAAnZ" + }, + "source": [ + "
\n", + "\n", + "
\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Nwq35q96AJV7" + }, + "source": [ + "A simplified version is a Contour plot, where each line shows values of $\\Theta_0$ and $\\Theta_1$ that yield the same value of the cost function $J$:\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "JxsQ-QiZAMvS" + }, + "source": [ + "
\n", + "
\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "DQ1XipNQAVtu" + }, + "source": [ + "# Gradient Descent Algorithm\n", + "\n", + "The Gradient Descent Algorithm can be used to solve the Linear Regression problem (and also address many other problems):\n", + "\n", + "Main idea is to start with arbitrary values for $\\Theta_0$ and $\\Theta_1$, and then repeatedly update $\\Theta_0$ and $\\Theta_1$ such that the cost $J(\\Theta_0, \\Theta_1)$ becomes smaller and smaller, until we hopefully obtain the minimal (optimal) value.\n", + "\n", + "More formally, we can write this as follows:\n", + "\n", + "> repeat until convergence\n", + "\n", + ">> $\\Theta_j := \\Theta_j - \\alpha \\frac{\\partial}{\\partial \\Theta_j} J(\\Theta_0, \\Theta_1)$, (for j=0 and j=1)\n", + "\n", + "\n", + "Here, $\\alpha$ is the Learning Rate of the algorithm. If we choose $\\alpha$ too large, we might overshoot the minimum, and the algorithm might not converge, or even diverge.\n", + "\n", + "Calculating the derivatives of $J(\\Theta_0, \\Theta_1)$ (not shown here) and plugging them into the Gradient Descent Algorithm yields the following update function:\n", + "\n", + "> repeat until convergence\n", + "\n", + ">> $\\Theta_0 := \\Theta_0 - \\alpha \\frac 1m \\sum_{i=1}^m (h_\\Theta(x^{(i)}) - y^{(i)})$\n", + "\n", + ">> $\\Theta_1 := \\Theta_1 - \\alpha \\frac 1m \\sum_{i=1}^m (h_\\Theta(x^{(i)}) - y^{(i)}) x^{(i)}$\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "wZfSi0YrjLbp" + }, + "source": [ + "# Calculating the Partial Derivatives of $J(\\Theta_0, \\Theta_1)$ [Not Part of Exam]\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "iQUH2yyijfbl" + }, + "source": [ + "If you want to know HOW these partial derivaties are calculated, you can checkout section \"Derivations of the partial derivatives w.r.t $\\Theta_0$, $\\Theta_1$\" of the blogpost at https://medium.com/swlh/the-math-of-machine-learning-i-gradient-descent-with-univariate-linear-regression-2afbfb556131 - which provides by itself a very detailed explanation how Linear Regression works." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3QW1peeTom5G" + }, + "source": [ + "# Remarks and Extensions (NOT in the videos!):\n", + "\n", + "* Linear Regression with one variable is also called \"Univariate Linear Regression\"\n", + "\n", + "* Even if variables x and y are related, variable x does not necessarily ***cause*** variable y.\n", + "\n", + "* For Linear Regression with one variable, we can also explicitly calculate the optimal solution for $\\Theta_0$ and $\\Theta_1$. Later on, we will look into Multivariate Linear Regression (with more than one input variables), where this will be much harder.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "NplZvs0jv9yG" + }, + "source": [ + "# Multivariate Linear Regression\n", + "If we do not only have one input variable (like size of a house), but multiple input variables (e.g. size of a house, number of floors, age of the house etc.), we can use **Multivariate** Linear Regression to predict the output values (e.g. the price of the house).\n", + "\n", + "Multivariate Linear Regression is a straightforward extension of Univariate Linear Regression, as is explained in the following videos (again by Andres Ng):\n", + "\n", + "\n", + "* Video 1: https://www.youtube.com/watch?v=Q4GNLhRtZNc&list=PLLssT5z_DsK-h9vYZkQkYNWcItqhlRJLN&index=18\n", + "\n", + "* Video 2: https://www.youtube.com/watch?v=pkJjoro-b5c&list=PLLssT5z_DsK-h9vYZkQkYNWcItqhlRJLN&index=19\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "YhEjHIUYxJPd" + }, + "source": [ + "# Main Concepts for Multivariate Linear Regression\n", + "\n", + "**Definition:** *Multivariate Linear Regression*\n", + "\n", + "Given a set of $m$ training samples $(x^{(i)}, y^{(i)})$, where each sample $x^{(i)}$ consists of n measurements $x_1^{(i)}, x_2^{(i)}, ..., x_n^{(i)}$, and $y^{(i)}$ is the output value of the sample. We define the **Hypothesis** $h_\\Theta(x) = \\Theta_0 x_0 + \\Theta_1 x_1 + ... + \\Theta_n x_n = \\Theta^T x$ with $x_0 = 1$\n", + "\n", + "Our goal in Multivariate Linear Regression is to find values for $\\Theta_0, \\Theta_1, ... \\Theta_n$ such that $h_\\Theta(x^{(i)})$ is close to $y^{(i)}$ for each sample $(x^{(i)},y^{(i)})$.\n", + "\n", + "\n", + "**Definition:** *Cost Function*\n", + "$J(\\Theta_0, \\Theta_1, ..., \\Theta_n) = \\frac{1}{2m} \\sum_{i=1}^m (h_\\Theta(x^{(i)}) - y^{(i)})^2$\n", + "\n", + "**Gradient Descent Algorithm:**\n", + "> Repeat until convergence:\n", + ">> $\\Theta_j := \\Theta_j - \\alpha \\frac 1m \\sum_{i=1}^m (h_\\Theta(x^{(i)}) - y^{(i)}) x_j^{(i)}$\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "bu4EH0JSpIGl" + }, + "source": [ + "# Trivia: Who invented it - One of the first feuds in modern mathematics [Not Part of Exam]\n", + "\n", + "Apparently, both Gauss and Lagrange claimed in the end of the 18th century that they had \"invented\" the idea of least square regression. The blogpost at https://medium.com/swlh/the-math-of-machine-learning-i-gradient-descent-with-univariate-linear-regression-2afbfb556131 has a nice discussion of this topic." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ekYnK897IXMr" + }, + "source": [ + "# Trivia: Why is it called \"Regression\"? [Not part of Exam]\n", + "According to https://people.duke.edu/~rnau/regintro.htm, the term regression was first used by Francis Galton around 1877:\n", + "\n", + "> \"Galton was a pioneer in the application of statistical methods to measurements in many branches of science, and in studying data on relative sizes of parents and their offspring in various species of plants and animals, he observed the following phenomenon: a larger-than-average parent tends to produce a larger-than-average child, but the child is likely to be less large than the parent in terms of its relative position within its own generation ... Galton termed this phenomenon a regression towards mediocrity, which in modern terms is a regression to the mean.\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "dRnIczkEKHow" + }, + "source": [ + "![image 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)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "MFkjjmG2vUh6" + }, + "source": [ + "Picture of a regression line illustrating this effect, from a lecture presented by Galton in 1877 (from: https://people.duke.edu/~rnau/regintro.htm)\n" + ] + } + ], + "metadata": { + "colab": { + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + }, + "language_info": { + "name": "python" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} \ No newline at end of file