Because the tree-building algorithm computes the overall statistical ... the training data and predict poorly on new data. That said, every problem scenario is different, and many decision tree models ...

A binary classification problem is one where the goal is to predict the value ... Starting with all 200 training items, the decision tree algorithm scans the data and finds the one value of the one ...

Decision trees naturally support classification problems with more than two classes ... trees are grown by a randomized tree-building algorithm. The training set is sampled with replacement ...

What are the advantages of logistic regression over decision trees ... two optimization algorithms are equivalent when their performance is averaged across all possible problems.

The recent study highlights how training data can skew a decision-making algorithm in unexpected ways—in addition to the known problem of biased training data. For example, in a separate study ...

Four years of research led to a specific decision tree data mining algorithm yielding best results. Results obtained from the BC database were excellent, revealing $4.7 billion (US) in high ...