Bullet Points

Bullet Points

This post lists out various topics under the machine learning subject.

Data

• data modalities
  • numbers
  • texts
  • images
  • videos
  • audios
• data cleaning
• imbalanced data
• data normalization (one pitfall)
  • standardization
• data augmentation
• data splitting
  • cross validation
  • RANSAC
• feature extraction/engineering
  • domain expertise
  • kernel method

Model

• supervised vs. unsupervised
  • supervised learning
    • classification
      • logistic regression
      • support vector machine
      • Bayes classifier
      • linear discriminant analysis
    • regression (linear and non-linear case)
  • unsupervised learning
    • discovers inherent properties (latent variables) in the data
    • includes
      • clustering
      • dimensionality reduction/manifold embedding
      • anomaly detection
      • latent-variable model
        • hidden Markov model
        • independent component analysis
• discriminative vs. generative
• classification vs. regression
  • from classification model to regression model
  • from binary classification to multi-class classification
• linear vs. non-linear
• parametric vs. non-parametric
• ensemble method
  • bootstrap aggregating
    • random forest
  • gradient boosting
    • least square boosting
    • AdaBoost
    • LogitBoost
• regularization and overfitting

Evaluation

• training criterion

  • mean squared error
  • cross entropy
  • impurity
    • Gini index
    • entropy

• testing criterion

  • confusion matrix

    Real\Pred	Positive	Negative
    Positive	TP	FN
    Negative	FP	TN

    • accuracy
    • precision
    • recall
    • F-score

  • precision-recall curve

  • receiver operation curve

  • mean average precision