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
- Support vector machine
- Least squares support vector machines

- Quadratic classifier
- Kernel estimation
- Boosting (meta-algorithm)
- Decision tree
- Neural network
- FMM Neural Network
- Learning vector quantization

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