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Hi,
I noticed that the TreeExplainer only supports sklearn, xgboost, lightgbm, and catboost models, is there anyway to introduce a Tree ensemble other than the supported models ?
I am currently …
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I can build a model using RandomForest but i can't get the scores because i get some errors.
If i run with --tree-type=RegressionTree
> Exception in thread "main" java.lang.NumberFormatException:…
ghost updated
7 years ago
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Now that we have ensembles in core H2O, it would probably be best to move the h2oEnsemble R package to it's own repo. It's currently located as a subfolder of the h2o-r folder in h2o-3: https://github…
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This is an ensemble tree-based method similar to random forest but with more regularisation. In my experience, it works better than random forest
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Hello, in the Monoforest paper (end of Section 4) it is mentioned that it's possible to take a model trained in LightGBM and transform it to "to an ensemble of symmetric trees", which I assume are obl…
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I'm trying to build an ensemble learner using PiecewiseTreeRegressors. In doing so, the parameter "sample_weight" is utilized during fitting of the estimator. This throws an error here:
https://githu…
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Hello and thanks you for that package.
I came across a problem while trying to use a xgboost model that was trained on dataframe.
So this is my code:
```
X_train, X_test, y_train, y_test = load_c…
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I am planning on submitting several PRs in an attempt to merge #5041 in slowly, with the ultimate goal being a clean implementation of multithreaded decision tree building so that Gradient Boosting ca…
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Hi @Magdoll,
I'm running the ANGEL v3.0 with the example data and I got the following error:
`$angel_predict.py test.fa MCF7_2015.dumb.final.training.pickle test_angel
Reading classifer pickle: M…