GitHub / vaitybharati / P27.-Supervised-ML---Multiple-Linear-Regression---Toyoto-Cars
Supervised-ML---Multiple-Linear-Regression---Toyota-Cars. EDA, Correlation Analysis, Model Building, Model Testing, Model Validation Techniques, Collinearity Problem Check, Residual Analysis, Model Deletion Diagnostics (checking Outliers or Influencers) Two Techniques : 1. Cook's Distance & 2. Leverage value, Improving the Model, Model - Re-build, Re-check and Re-improve - 2, Model - Re-build, Re-check and Re-improve - 3, Final Model, Model Predictions.
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PURL: pkg:github/vaitybharati/P27.-Supervised-ML---Multiple-Linear-Regression---Toyoto-Cars
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Language: Jupyter Notebook
Size: 3.54 MB
Dependencies parsed at: Pending
Created at: about 4 years ago
Updated at: almost 2 years ago
Pushed at: about 4 years ago
Last synced at: almost 2 years ago
Topics: collinearity-diagnostics, cooks-distance, correlation-analysis, eda, heteroscedasticity, homoscedasticity, influence-plot, leverage-value, multiple-linear-regression, ols-regression, python, residual-analysis, rsquare-values, scatter-plot, smf, statsmodels