Contents

Metrics

• Sensitivity
• Specificity
• Precision
• Recall

Regression

• Linear Methods
  • Linear Regression
  • Logistic Regression
  • Stochastic Gradient Descent
• Shrinkage methods
  • Ridge Regression
  • LASSO
  • LARS
• Derived Input Methods
  • Principal Components Regression
  • Partial Least Squares Regression
• Non-linear methods
  • MARS
  • Polynomial Regression
  • LOESS
  • Splines
  • Generalized Additive Models (GAMS)
  • Isotonic Regression

Classification

• Bayes error rate
• k Nearest Neighbors
• Linear Discriminant Analysis
• QDA
• Support Vector Machines

Tree-based Methods

• Decision Trees
• Bagging
• Random Forests
• Boosting

Model Selection / Assessment / Resampling

• Bias-Variance trade-off
• BIC
• MDL
• Vapnik-Chervonenkis Dimension
• Cross-validation
• Bootstrap

Clustering

• K-Means
• Gaussian Mixture Models
• Hierarchical Clustering
• Affinity Propagation
• Mean Shift
• Spectral Clustering
• DBSCAN
• Birch
• Power Iteration Clustering

Dimensionality Reduction

• PCA
• SVD
• ICA
• Factor Analysis

Density Estimation
Frequent Pattern Mining
Recommender Systems
NLP