Answer / Asha Verma

Decision tree classification is a popular machine learning algorithm used for classification tasks. It works by recursively partitioning the input space into smaller regions (nodes) based on the values of features, with each region corresponding to a class label. The decision tree is built by selecting the feature and threshold value that offer the best split at each step, often using criteria such as information gain or Gini impurity to guide the selection process.

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