Ayuda con linea Seleccion de variables – Boruta – python

Hola Jordi

Estoy intentando utilizar el codigo de la clase 603 con los datos de diabetes pero no logro sacar las iteraciones en el boruta.

Me dice que ya no se utiliza np.int en numpy

from boruta import BorutaPy
import numpy as np
from sklearn.ensemble import RandomForestClassifier

# definimos el random forest clasificador
randomForest = RandomForestClassifier(n_jobs = -1,class_weight=’balanced’, max_depth = 5)
randomForest.fit(X_, y_)

# define Boruta feature selection
feature_selection = BorutaPy(randomForest, n_estimators = ‘auto’, verbose = 1,
random_state = 16,max_iter= 200 )

# Get relevant features
feature_selection.fit(np.array(X_), np.array(y_))

— Me da el siguiente mensaje:
—————————————————————————
AttributeError Traceback (most recent call last)
<ipython-input-78-27d43754b480> in <cell line: 14>()
12
13 # Get relevant features
—> 14 feature_selection.fit(np.array(X_), np.array(y_))

2 frames
/usr/local/lib/python3.10/dist-packages/boruta/boruta_py.py in fit(self, X, y)
199 «»»
200
–> 201 return self._fit(X, y)
202
203 def transform(self, X, weak=False):

/usr/local/lib/python3.10/dist-packages/boruta/boruta_py.py in _fit(self, X, y)
258 # 1 – accepted in original code
259 # -1 – rejected in original code
–> 260 dec_reg = np.zeros(n_feat, dtype=np.int_)
261 # counts how many times a given feature was more important than
262 # the best of the shadow features

/usr/local/lib/python3.10/dist-packages/numpy/__init__.py in __getattr__(attr)
317
318 if attr in __former_attrs__:
–> 319 raise AttributeError(__former_attrs__[attr])
320
321 if attr == ‘testing’:

AttributeError: module ‘numpy’ has no attribute ‘int’.
np.int was a deprecated alias for the builtin int. To avoid this error in existing code, use int by itself. Doing this will not modify any behavior and is safe. When replacing np.int, you may wish to use e.g. np.int64 or np.int32 to specify the precision. If you wish to review your current use, check the release note link for additional information.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations