fModel types

Compare prediction methods including linear regression, decision trees, random forests, and neural networks. — 8 entries

Predict a continuous value with a weighted sum of inputs.

Turn a weighted score into a probability for binary classification.

Repeatedly split data with feature questions.

Combine predictions from many varied decision trees.

Predict from the k closest stored examples.

Compose layers of weighted sums and nonlinear transforms.

Weight information from other positions when representing one position.

Control how peaked a softmax probability distribution becomes.