Xgboost feature importance

import matplotlib.pyplot as plt
from xgboost import plot_importance, XGBClassifier # or XGBRegressor

model = XGBClassifier() # or XGBRegressor

# X and y are input and target arrays of numeric variables
model.fit(X,y)
plot_importance(model, importance_type = 'gain') # other options available
plt.show()
# if you need a dictionary 
model.get_booster().get_score(importance_type = 'gain')

Similar codes

0 vote219 views1 answer
Which env im running jupyter notebook
Python
1 vote193 views4 answers
Django query or condition for query parameters
Python
0 vote186 views1 answer
Python tar a directory
Python
0 vote174 views1 answer
Is plaindrome python
Python
52 votes232 views2 answers
Index in list
Python
0 vote177 views1 answer
Jinja flask
Python Flask
11 votes176 views1 answer
Python discord
Python
5 votes219 views3 answers
How to hide command console python
Python
0 vote182 views3 answers
Groupby fillna
Python
0 vote180 views1 answer
Enumerate in range python
Python