资源汇总
Kaggle列出来的资源
- PastSolutions是过期的竞赛的code和解决方案
- 非官方的维持的是PastSolutions
- 官方对于常用的算法的解释列表:
Linear Regression
Logistic Regression
K Nearest Neighbors
Support Vector Machines
Random Forests - has performed very well on many competitions
Neural Networks
Ensembling
Elastic Net
Mean Shift
Introduction To Mean Shift Algorithm
April 1, 2010 by Saravanan Thirumuruganathan
核方法
随机森林
关于机器学习官方列出的资源How do I learn Machine Learning?
话题链接
kaggle_president_jeremy_howard的访谈
中提到Random Forests是一种很好的方法，不需要动脑筋
The nice thing about algorithms like the random forest is that you can chuck as many crazy ideas at them as you like, and the algorithms figure out which ones work.
The algorithms tell you what's important and what's not. You might ask why those things are important, but I think that's less interesting. You end up with a predictive model that works. There's not too much to argue about there.
