Machine Learning Regression Techniques

These flashcards cover essential vocabulary and definitions related to regression techniques discussed in machine learning.

Multiple Linear Regression

A statistical technique that uses multiple independent variables to predict the value of a dependent variable.

p-value

The probability that the observed data is due to chance; a p-value less than 0.05 indicates statistical significance.

Backward Elimination

A variable selection method starting with all candidate variables and removing the least significant variable iteratively.

Forward Selection

A variable selection method starting with no variables and adding the most significant variable at each step.

Stepwise Selection

A variable selection method that combines both backward elimination and forward selection processes.

Standard Deviation Reduction

A measure used in decision trees to determine how much variance is reduced after a dataset is split.

Decision Tree Regression

A regression method that predicts a target variable by learning simple decision rules inferred from the data features.

Polynomial Regression

A type of regression analysis that models the relationship between the independent variable x and the dependent variable y as an nth degree polynomial.

R-squared

A statistical measure that represents the proportion of the variance for the dependent variable that's explained by the independent variables in a regression model.

IEEE Format

A set format for writing technical documents, standardized by the Institute of Electrical and Electronics Engineers.