Siksha Sarovar

Siksha Sarovar (sikshasarovar.com) is a free educational web application that helps students in India learn programming and prepare for academic and competitive exams. The platform offers structured coding courses (C, C++, Python, Java, HTML, CSS, PHP, Power BI, AI, Machine Learning, Data Science), complete university curriculum notes for BCA/MCA students with previous year question papers, Class 10 and Class 12 CBSE/HBSE school notes, and dedicated preparation material for SSC, UPSC, Banking, Railway and other government exams. Browsing the site is completely free and requires no account. Users may optionally sign in with Google solely to save their learning progress, quiz scores and personal preferences across devices.

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Siksha Sarovar is a free e-learning platform for coding courses, BCA university notes and competitive exam preparation. Optional Google sign-in saves your learning progress across devices.

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7. Supervised Learning – Regression

Lesson 7 of 21 in the free Machine Learning notes on Siksha Sarovar, written by Rohit Jangra.

What is Regression?

Regression analysis is a set of statistical processes for estimating the relationships among variables. In ML, it is used to predict a continuous outcome variable (y) based on one or more predictor variables (x).

Goal: Predict a specific value (e.g., House Price, Stock Value, Temperature).

Simple Linear Regression

The "Hello World" of ML. It fits a straight line (y = mx + c) that minimizes the error between predicted vs actual values.

  • m: Slope (coefficient)
  • c: Intercept

Polynomial Regression

Used when the data doesn't form a straight line. It fits a curve to the data by using higher-order powers of x (x^2, x^3).

Evaluation Metrics for Regression

How do we know our model is good?

  1. MAE (Mean Absolute Error): Average of absolute differences. Easy to interpret.
  2. MSE (Mean Squared Error): Average of squared differences. Punishes large errors more.
  3. R² Score (Coefficient of Determination): How well the data fits the regression line (0 to 1). 1 is perfect.