Who introduced the alternating decision tree algorithm?
Yoav Freund and Llew Mason introduced the alternating decision tree algorithm in a research paper. Their initial presentation contained several typographical errors that confused early readers.
Questions about Alternating decision tree
Short answers, pulled from the story.
How does an instance traverse an alternating decision tree compared to binary classification trees?
An instance traverses all paths where every decision node evaluates as true within an ADTree instead of following only one path per instance like CART or C4.5. This structure differs from binary classification trees which follow only one path per instance.
What software tools provide functional implementations of the alternating decision tree process?
Software tools named Weka and JBoost provide functional implementations of the alternating decision tree process. Researchers constructed examples using JBoost on the spambase dataset available from the UCI Machine Learning Repository.
How are prediction nodes structured within an alternating decision tree?
Prediction nodes appear at both root positions and leaf positions throughout the entire tree. Decision nodes specify predicate conditions while prediction nodes hold single numerical values.
Why do misclassified instances receive larger weights during boosting iterations?
Data receives different distributions at each iteration with misclassified instances gaining larger weights. Accurately classified instances receive reduced weight in subsequent rounds of processing.