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How can I get the variable importance matrix (mean decrease in impurity GINI) for all the predictors used to train an extraTrees model. I'm looking into the R package but I didn't found any function t…
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**Describe the bug**
Getting different results by turning on/off sklearnex with ExtraTrees and RandomForest algorithms.
This issue occurs starting with version 2024.1. I found it with my own dataset…
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**Describe the bug**
a function *export_graphviz()* returns `ValueError: cannot convert float NaN to integer` error on ExtraTrees and RandomForest classifier algorithms after Intelex patching.
``…
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### Summary
While missing-value support for decision trees have been added recently, they only work when encoded in a dense array. Since `RandomForest*` and `ExtraTrees*` both support sparse `X`, if …
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val seedBarley = Natura:barley.seed:0;
val grainWheat = ExtraTrees:misc:8;
val grainBarley = ExtraTrees:misc:9;
val grainRye = ExtraTrees:misc:10;
val grainCorn = ExtraTrees:misc:11;
recipes.removeSh…
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**Is your feature request related to a problem? Please describe.**
SKlearn provides training and inference for ExtraTrees regression/classification.
https://scikit-learn.org/stable/modules/generate…
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scikit-learn 1.4 [adds native missing value handling for RandomForest](https://scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_4_0.html#missing-value-support-for-ran…
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Version used: 2021.5.1
The following model gets a speedup with `predict_proba`:
```
from sklearnex.ensemble import RandomForestClassifier
model = RandomForestClassifier(..., criterion="gini")
…
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### Describe the workflow you want to enable
Currently, random/extra forests can bootstrap sample the data such that `max_samples \in (0.0, 1.0]`. This enables an out-of-bag sample estimate in fore…
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