Machine Learning: Regression with GraphLab Create

bias-variance trade-off gradient descent
Ridge regression        cross-validation      measure of fit + measure of  model complexity  
Lasso regression coordinate descent feature selection measure of fit + (different) measure of model complexity
Nearest Neighbor Regression & Kernel Regression
 
concave  hax Max value
convex  has Min value
Models

 

• Linear regression
• Regularization: Ridge (L2), Lasso (L1)
• Nearest neighbor and kernel regression
Algorithms • Gradient descent
• Coordinate descent
Concepts

 

• Loss functions, bias-variance tradeoff,

cross-validation, sparsity, overfitting,

model selection, feature selection

 

 

 

 

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