Statistical classification

lastmod 2026-07-31created 2015-12-233 edits

In machine learning and statistics, classification is the problem of identifying to which of a set of categories (sub-populations) a new observation belongs, on the basis of a training set of data containing observations (or instances) whose category membership is known. An example would be assigning a given email into "spam" or "non-spam" classes or assigning a diagnosis to a given patient as described by observed characteristics of the patient (gender, blood pressure, presence or absence of certain symptoms, etc.).

Categories

• Gradient descent-based algorithms
  • Logistic Regression
  • SGD Classifier
  • Artificial Neural Networks (ANNs; neural networks)
• Probability-based algorithms
  • LDA (Linear Discriminant Analysis)
  • QDA (Quadratic Discriminant Analysis)
  • Naive Bayes Classifier
• Distance-based algorithms
  • K-Nearest Neighbor (K-NN)
  • Support Vector Machine (SVM)
• Tree-based algorithms
  • Decision Tree
  • Ensemble-based
    • Random Forest (bagging)
    • AdaBoost
    • Gradient Boosting Tree (GBT)
    • lightGBM
    • XGBoost
    • CatBoost

See also

• Machine learning

Favorite site

• Wikipedia (en) Description of statistical classification
• (ML) Classification Model