Feature Importances using Extra Trees in sklearn

by | Jan 13, 2023 | AI, Machine Learning and Deep Learning, Machine Learning Using Python, Python Scikit-learn

We can use the Extra Trees to get the feature importances of various features of a dataset. These feature importances are impurity-based feature importances. Please note that impurity-based feature importances are strongly biased. They favor numerical features over binary or categorical features with a small number of categories.

We can use the following Python code to get the feature importance of various features in the Pima Indians Diabetes dataset.

from sklearn.ensemble import ExtraTreesClassifier
import pandas

data = pandas.read_csv("diabetes.csv")
D = data.values

X = D[:, :-1]
y = D[:, -1]

classifier = ExtraTreesClassifier(n_estimators=100)
classifier.fit(X, y)

print(classifier.feature_importances_)

Here, firstly, we are reading the Pima Indians Diabetes dataset. The last column of the dataset specifies the target variable. So, after reading the dataset, we are splitting the columns of the dataset into features and the target…

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Amrita Mitra

Author

Ms. Amrita Mitra is an author, who has authored the books “Cryptography And Public Key Infrastructure“, “Web Application Vulnerabilities And Prevention“, “A Guide To Cyber Security” and “Phishing: Detection, Analysis And Prevention“. She is also the founder of Asigosec Technologies, the company that owns The Security Buddy.

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