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

관련정보

# Table of Contents

# Incoming Links #

## Related Datasets (Dataset 0) #

## Related Articles (Article 1) #

## Related Codes (Code 2) #

# Suggested Pages #

- 0.241 Keras
- 0.122 Computer vision
- 0.078 Feature extraction
- 0.067 PCA
- 0.044 Hidden Markov model
- 0.028 Linear discriminant analysis
- 0.025 로지스틱 회귀
- 0.024 Scikit Flow
- 0.024 Mathematics
- 0.024 Single-linkage clustering
- More suggestions...