Statistical classification

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

• 경사하강법 기반 알고리즘
  • Logistic Regression
  • SGD Classifier
  • Artificial Neural Networks (ANNs; 신경망)
• 확률 기반 알고리즘
  • LDA (Linear Discriminant Analysis)
  • QDA (Quadratic Discriminant Analysis)
  • Naive Bayes Classifier
• 거리 기반 알고리즘
  • K-Nearest Neighbor (K-NN)
  • Support Vector Machine (SVM)
• 트리기반 알고리즘
  • Decision Tree
  • 앙상블 기반
    • Random Forest (배깅)
    • AdaBoost
    • Gradient Boosting Tree (GBT)
    • lightGBM
    • XGBoost
    • CatBoost

See also

• Machine learning

Favorite site

• Wikipedia (en) 통계적 분류에 대한 설명
• (ML) 분류 모델(Classification Model)