Concept
Multicollinearity
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Explores multilinear regression, variance, correlation, optimization, ANOVA, and design procedures.
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Explores advanced concepts in linear regression models, including multicollinearity, hypothesis testing, and handling outliers.
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Explores the dangers of multicollinearity in linear models and discusses diagnostic methods and remedies.
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Introduces nonlinear ML algorithms, covering nearest neighbor, k-NN, polynomial curve fitting, model complexity, overfitting, and regularization.
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