Machine Learning in Action:KNN Algorithm
概述 对于分类问题，最主要的任务就是找到对应数据合适的分类。而机器学习的另外一项任务就是回归，好比CTR预测之类的。ml算法按照有无label能够分为有监督学习和无监督学习，对于无监督学习的算法比较经典的有聚类算法，有监督的相对来讲较多，回归类算法基本都是的。按照参数有能够划分红有参数模型和无参数模型和半参数模型，有参数模型有两个特征，一个是用参数表明从训练数据中得到的信息，只有当target f
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相关文章
- 1. Machine Learning in Action:KNN Algorithm
- 2. Machine learning in action (2) —— KNN algorithm
- 3. Machine Learning(8): Reinforcement learning algorithm
- 4. Machine Learning Series No.6 -- EM algorithm
- 5. Machine Learning - Coursera week6 Evaluating a learning algorithm
- 6. Machine Learning in Action (5) —— logistic regression
- 7. Machine Learning in Action (1) —— basics
- 8. Machine Learning in Action:Decision Tree
- 9. [Machine Learning]--Improving classification with the AdaBoost meta-algorithm
- 10. [Machine Learning & Algorithm] 随机森林（Random Forest）