Machine Learning in Action:KNN Algorithm
概述 對於分類問題，最主要的任務就是找到對應數據合適的分類。而機器學習的另外一項任務就是迴歸，好比CTR預測之類的。ml算法按照有無label能夠分爲有監督學習和無監督學習，對於無監督學習的算法比較經典的有聚類算法，有監督的相對來講較多，迴歸類算法基本都是的。按照參數有能夠劃分紅有參數模型和無參數模型和半參數模型，有參數模型有兩個特徵，一個是用參數表明從訓練數據中得到的信息，只有當target f
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相關文章
- 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] 隨機森林（Random Forest）