# 分类问题

## Classification

• 线性分类器
• 线性判别分析(LDA)
• 逻辑回归(logistic regression)
• 朴素贝叶斯分类器(naive bayes classifier)
• 感知器(perceptron)
• 支持向量机(support vector machine)
• 最小二乘支持向量机(least squares support vector machines )
• 核估计(kernel estimation)
• 最近邻居法(k-nearest neighbor)
• Boosting算法
• 决策树(decision trees)
• 随机森林(random forests)
• 神经网络(neural networks)
• 学习式向量量化(learning vector quantization)

[描述来源：Wikipedia URL：https://en.wikipedia.org/wiki/Statistical_classification

## 发展历史

### 主要事件

 年份 事件 相关论文 1936 Fisher提出著名的Fisher Discriminat Analysis Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of human genetics, 7(2), 179-188. 1943 McCulloch等人首次提出了一个基于神经网络的计算模型，开启了人工神经网络的应用 McCulloch, Warren; Walter Pitts (1943). "A Logical Calculus of Ideas Immanent in Nervous Activity". Bulletin of Mathematical Biophysics. 1957 Rosenblatt提出了感知器方法 Rosenblatt, F. (1957). The perceptron, a perceiving and recognizing automaton Project Para. Cornell Aeronautical Laboratory. 1958 Cox提出逻辑回归算法 Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society. Series B (Methodological), 215-242. 1963 Vapnik提出支持向量机算法 Vapnik, V. (1963). Pattern recognition using generalized portrait method. Automation and remote control, 24, 774-780. 1967 Cover等人提出最近邻居分类算法 Cover, T., & Hart, P. (1967). Nearest neighbor pattern classification. IEEE transactions on information theory, 13(1), 21-27. 1988 Kearns提出将弱分类器转变成强分类器的Boosting思想 Kearns, M. (1988). Thoughts on hypothesis boosting. Unpublished manuscript, 45, 105. 1995 Ho提出随机森林算法 Ho, T. K. (1995, August). Random decision forests. In Document Analysis and Recognition, 1995., Proceedings of the Third International Conference on (Vol. 1, pp. 278-282). IEEE. 1995 Russell等人第一次对贝叶斯分类方法作了正式介绍 Russell, Stuart; Norvig, Peter (2003) [1995]. Artificial Intelligence: A Modern Approach (2nd ed.), 488 1999 Suykens等人提出最小二乘支持向量机 Suykens, J. A., & Vandewalle, J. (1999). Least squares support vector machine classifiers. Neural processing letters, 9(3), 293-300.

## 发展分析

### 未来发展方向

Contributor: Keyu Qi