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Add support for Gamma regression (#1258)

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* Add support for Gamma regression

* Use base_score to replace the lp_bias

* Remove the lp_bias config block

* Add a demo for running gamma regression in Python

* Typo fix

* Revise the description for objective

* Add a script to generate the autoclaims dataset
This commit is contained in:
Shengwen Yang
2016-07-07 01:22:46 +08:00
committed by Tianqi Chen
parent f74e2439e0
commit 77d17f6264
5 changed files with 181 additions and 0 deletions
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doc/parameter.md
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@@ -119,6 +119,7 @@ Specify the learning task and the corresponding learning objective. The objectiv
- "multi:softmax" --set XGBoost to do multiclass classification using the softmax objective, you also need to set num_class(number of classes)
- "multi:softprob" --same as softmax, but output a vector of ndata * nclass, which can be further reshaped to ndata, nclass matrix. The result contains predicted probability of each data point belonging to each class.
- "rank:pairwise" --set XGBoost to do ranking task by minimizing the pairwise loss
- "reg:gamma" --gamma regression for severity data, output mean of gamma distribution
* base_score [ default=0.5 ]
- the initial prediction score of all instances, global bias
- for sufficent number of iterations, changing this value will not have too much effect.