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Linear regression and logistic regression can't display collaborations between highlights. The Classification And Regression Trees (CART) algorithm is the most straightforward and famous tree algorithm, and models a basic collaboration between highlights
To fabricate the tree, we pick each time the element that parts our information the most ideal way that is available. How would we measure the qualitiy of a split ? We apply rules, for example, the cross-entropy or Gini pollutant. We stop the improvement of the tree while parting a hub doesn't bring down the debasement
To implement decision trees in Python, we can use scikit-learn:
clf = DecisionTreeClassifier(max_depth=3) clf.fit(X_train, y_train) y_pred = clf.predict(X_test) accuracy_score(y_pred, y_test) 0.9210526315789473
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In Conversation With Dr Suman Sanyal, NIIT University,he shares his insights on how universities can contribute to this highly promising sector and what aspirants can do to build a successful data science career.
The biggest problem we face today is the commoditization of education. Individuals and corporations alike would like quality courses to be offered by the best faculty at the lowest price