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

6 votes104 views1 answer
How to get username with userid discord.py
Python
1 vote115 views1 answer
Convert pdf to base64 python
Python
1 vote128 views1 answer
How to search where a character is in an array in python
Python
2 votes147 views1 answer
Import validation error in django
Python Django
0 vote123 views1 answer
Get the mean of all not nan values
Python
0 vote122 views1 answer
Element assignment numpy matrix
Python
1 vote108 views1 answer
Django bulk update
Python
1 vote149 views1 answer
Django set default value for model not form
Python Django
0 vote132 views1 answer
AttributeError: 'psycopg2.extensions.Column' object has no attribute '_asdict'
Python
0 vote147 views1 answer
A int and float python
Python