Youtor
Random Forest based Classification
>> YOUR LINK HERE: ___ http://youtube.com/watch?v=ajTc5y3OqSQ
[For Detailed - Chapter-wise Machine learning tutorial - please visit (https://ai-leader.com/machine-learning/ )] • [For Detailed - Chapter-wise Deep learning tutorial - please visit (https://ai-leader.com/deep-learning/ )] • This tutorial explains the Random Forest algorithm with a very simple example. Random Forest algorithm has gained a significant interest in the recent past, due to its quality performance in several areas. • The random forest algorithm discussed in this tutorial is based on the following references: • 1. Breiman L (2001). Random Forests . Machine Learning. 45 (1): 5–32. doi:10.1023/A:1010933404324. • 2. Ho TK (1998). The Random Subspace Method for Constructing Decision Forests (PDF). IEEE Transactions on Pattern Analysis and Machine Intelligence. 20 (8): 832–844. doi:10.1109/34.709601 • 3. Gareth James; Daniela Witten; Trevor Hastie; Robert Tibshirani (2013). An Introduction to Statistical Learning. Springer. • 4. Breiman L, Ghahramani Z (2004). Consistency for a simple model of random forests . Statistical Department, University of California at Berkeley. Technical Report (670) • 5. Dietterich, Thomas (2000). An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization . Machine Learning: 139–157
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