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I haven't dug in here to see if this is by design, but `GradientBoosting*.estimators_` is an ndarray of 1d ndarrays containing `DecisionTreeRegressor`s. The other tree ensemble methods have lists of t…
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```
What steps will reproduce the problem?
1. convert sample-ranking-data to binary format
2. train with sample-ranking-data using sample-ranking-config.properties
What is the expected output? What d…
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Example behavior:
```
>>> X = np.array(['No', 'Yes'], dtype=np.dtype('O'))
>>> utils.multiclass.type_of_target(X)
'unknown'
```
It does this because of explicit rule `y.dtype == object` that means t…
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The following parameters should be renamed for consistency:
- ~~`learn_rate` in GradientBoosting to `learning_rate`~~
- ~~`n_atoms` to `n_components` (right?) everywhere~~
- ~~`max_iters` to `max_iter…