boruta_py

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My point is that with a few simple code additions, BorutaPy could implement nearly the same interface as RFE (and the other predictors) and thus be more sklearn consistent.

pjcpjc

Does boruta apply to time series data?

1

Hello, I found Boruta really helpful in boosting my model performance. However, I have a question that can Boruta apply to time series data?

kkckk1110

AttributeError: module 'numpy' has no attribute 'int'. `np.int` was a deprecated alias for the builtin `int`.

13

This happens when the fit method is used

jorgesolerrr

BorutaPy selects different features in different iterations

1

First of all thanks for the package, I've been using it a lot in my work. I came up to something strange. I know Boruta selects everything that is important....

VEZcoding

AttributeError: module 'numpy' has no attribute 'bool' when using BorutaPy with RandomForestClassifier

3

I encountered an error while using BorutaPy with a RandomForestClassifier model. The error message states "AttributeError: module 'numpy' has no attribute 'bool'." The error suggests that BorutaPy is trying to...

codewithawr

I encountered an error while using BorutaPy with a LogisticRegression model. The issue arises when setting the n_estimators parameter to 'auto' in BorutaPy. The LogisticRegression model does not have the...

codewithawr

AttributeError: module 'numpy' has no attribute 'int'.

9

When I run this: `boruta.fit(Xtrn, yTrn)` I get the error message below, indicating that boruta_py isn't compatible with numpy versions greater than 1.20. I had numpy version 1.24.2 installed. So...

notuntoward

TypeError: BorutaPy.__init__() got an unexpected keyword argument 'early_stopping'

1

Looks like the [early_stopping](https://github.com/scikit-learn-contrib/boruta_py/blob/f783995eac12442af0c2b288368ae0802d4bea51/boruta/boruta_py.py#L204) parameter wasn't used. ```` def __init__(self, estimator, n_estimators=1000, perc=100, alpha=0.05, two_step=True, max_iter=100, random_state=None, verbose=0, early_stopping=False, n_iter_no_change=20): self.estimator = estimator self.n_estimators = n_estimators self.perc = perc self.alpha...

arilwan

Kaggle n_estimators issue with DecisionTreeClassifier

2

Here's my code snippet from Kaggle notebook: ``` rf_cl = RandomForestClassifier() dt_cl = DecisionTreeClassifier() estimator = dt_cl feat_selector = BorutaPy( verbose=2, estimator=estimator, n_estimators='auto', max_iter=20 ) feat_selector.fit(np.array(train_set_final), np.array(train_set_labels)) ``` Here's the...

MarcinKamil84

It would be useful to be able to capture this to get a relative sense of feature importance. If I understand correctly, it would also enable one to see the...

rwjmiller