added general README #196
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added general README #196
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fukatani
reviewed
Jul 15, 2018
| Regularized Greedy Forest (RGF) is a tree ensemble machine learning method described in [this paper](https://arxiv.org/abs/1109.0887). | ||
| RGF can deliver better results than gradient boosting decision tree (GBDT) on a number of datasets and it have been used to win some Kaggle competitions. | ||
| Unlike the traditional boosted decision tree approach, RGF directly works with the underlying forest structure. | ||
| RGF integrates two ideas: one is to include tree-structured regularization into the learning formulation; and the other is to employ the fully-corrective regularized greedy algorithm. |
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We'd better revise this expression by Rie Johnson or Tong Zhang.
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This description is taken from the original paper, so no need to do this.
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LGTM excepts above the comment. |
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Refer to #166.