In Machine learning and Statistics, classification (분류) 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. (https://en.wikipedia.org/wiki/Statistical_classification)

For Unsupervised learning, See Cluster analysis. And there are Binary classification, Multiclass classification. When Binary classification, we can evaluate the precision by ROC curve.

Examples of classification algorithms

• Linear classifier
  • Fisher's linear discriminant
  • Logistic regression
  • Naive Bayes classifier
  • Perceptron
• Support vector machine
  • Least squares support vector machines
• Quadratic classifier
• Kernel estimation
  • k-nearest neighbor
• Boosting (meta-algorithm)
• Decision tree
  • Random forest
• Neural network
• FMM Neural Network
• Learning vector quantization

관련정보

• scikit-learn에서 지원하는 분류 성능 평가 명령 데이터 사이언스 스쿨 2016-06-12

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