1.

Explain Dimensionality / Variable Reduction Techniques?

Answer»

Unsupervised Method (No Dependent Variable)

  1. Principal Component Analysis (PCA)
  2. Hierarchical Variable Clustering (Proc Varclus in SAS)
  3. Variance INFLATION FACTOR (VIF)
  4. Remove zero and near-zero variance predictors
  5. MEAN absolute CORRELATION. Removes the variable with the largest mean absolute correlation. 

Supervised Method (In RESPECT to Dependent Variable):

For Binary / Categorical Dependent Variable

  1. Information Value
  2. Wald Chi-Square
  3. Random Forest Variable Importance
  4. Gradient Boosting Variable Importance
  5. Forward/Backward/Stepwise - Variable Significance (p-value)
  6. AIC / BIC score

For Continuous Dependent Variable

  1. Adjusted R-Square
  2. Mallows' Cp Statistic
  3. Random Forest Variable Importance
  4. AIC / BIC score
  5. Forward / Backward / Stepwise - Variable Significance

Unsupervised Method (No Dependent Variable)

Supervised Method (In respect to Dependent Variable):

For Binary / Categorical Dependent Variable

For Continuous Dependent Variable


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