![]() Test_features_1_fruit = fruit_classifier.predict(test_features_1) Fruit classification with decision tree classifier Later use the build decision tree to understand the need to visualize the trained decision tree. To get a clear picture of the rules and the need for visualizing decision, Let build a toy kind of decision tree classifier. Later the created rules used to predict the target class. The decision tree classifier is a classification model that creates a set of rules from the training dataset. Implementing decision tree classifier in Python with Scikit-Learnīuilding decision tree classifier in R programming language How the decision tree classifier works in machine learning If new to the decision tree classifier, Please spend some time on the below articles before you continue reading about how to visualize the decision tree in Python. The above keywords used to give you the basic introduction to the decision tree classifier. You could aware of the decision tree keywords like root node, leaf node, information gain, Gini index, tree pruning. If you go through the article about the working of decision tree classifiers in machine learning. Now let’s look at the basic introduction to the decision tree.
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