Data Mining Methods(3)

Bilal Hussain Malik 

                                                       Data Mining Methods

                                                         Regression Analysis

Regression predicts constant outcomes by estimating dependencies between independent and dependent variables. Linear regression supports constant forecasting (e.g., house prices), while logistic regression estimates probabilities for binary outcomes. Applications include sales forecasting, risk assessment, and scientific modeling. The technique assumes linear relationships and normally distributed errors, with verification done with residual analysis. Regularization methods prevent overfitting in complex models. Regression provides quantifiable information about variable importance and effect sizes, so it is an essential tool for evidence-based business and research decision-making.