Information Gain and Feature Selection

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What is the primary goal of decision tree induction in classification?

To minimize the entropy of the child nodes

To split the data into the most homogeneous subsets possible (correct)

To maximize the probability of the parent node

To reduce the number of features used in the classification

What is the purpose of calculating the entropy in decision tree induction?

To determine the most important features in the classification

To evaluate the performance of the classification model

To measure the uncertainty of the classification (correct)

To decide the splitting criterion for the decision tree

What is the effect of overfitting in decision tree induction?

The decision tree becomes more complex and prone to errors (correct)

The decision tree becomes more accurate

The decision tree remains unchanged

The decision tree becomes less accurate

What is the purpose of tree pruning in decision tree induction?

To reduce the complexity of the decision tree and prevent overfitting Signup and view all the answers

What is the Gini impurity measure used for in decision tree induction?

To determine the best split for the decision tree Signup and view all the answers

What is the criterion used to decide when to stop splitting the data in decision tree induction?

When the entropy of the child nodes is zero Signup and view all the answers

What is the purpose of calculating information gain in decision tree induction?

To measure the goodness of a split in a classification rule Signup and view all the answers

What is the effect of entropy reduction on the decision tree induction process?

It helps to identify the most informative features and prevent overfitting Signup and view all the answers

What is the main purpose of tree pruning in decision tree induction?

To reduce the complexity of the decision tree and prevent overfitting Signup and view all the answers

What is the relationship between entropy and information gain in decision tree induction?

Information gain is a measure of entropy reduction, with higher information gain indicating lower entropy Signup and view all the answers

What is the effect of a balanced dataset on the entropy calculation in decision tree induction?

It decreases the entropy of the dataset, making it easier to classify Signup and view all the answers

What is the purpose of calculating the Gini impurity index in decision tree induction?

To measure the impurity of a node in the decision tree Signup and view all the answers

What is the primary goal of using the GainRatio(S, A) in decision tree induction?

To maximise the information gain for a feature Signup and view all the answers

What is the purpose of pruning a decision tree?

To prevent overfitting by removing unnecessary branches Signup and view all the answers

What is the Gini impurity index used for in decision tree induction?

To measure the impurity of a node in the decision tree Signup and view all the answers

What is the main advantage of using the SplitInformation(S, A) in decision tree induction?

It helps in selecting the best feature to split the data Signup and view all the answers

What is the primary cause of overfitting in decision trees?

Having a complex decision tree model Signup and view all the answers

What is the purpose of using the Gain(S, A) formula in decision tree induction?

To measure the information gain for a feature Signup and view all the answers

Information Gain and Feature Selection

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