Machine LearningDeep LearningComputer Science / Data
Supervised Learning
Linear Regression
Logistic Regression
Decision Trees
Random Forests
Support Vector Machine (SVM)
K-nearest neighbors (KNN)
Unsupervised Learning
K-means
Isolation Forest
Local Outlier Factor
Reinforcement Learning
Q-learning
SARSA
Libraries
Scikit-learn
Linear regression is a statistical method for studying the relationship between an explanatory variable Y (dependent variable) and one or more explanatory variables X (independent variables) in a linear and continuous manner.
The general form of a linear regression model is: Y = a + bX + ε where a is the ordinate at the origin, b is the slope of the line, and ε is the residual error.