Search Results:

Showing results 1 to 10 of 201.


Function predict.rotationForest [rotationForest v0.1.3]
keywords
classification
title
Predict method for rotationForest objects
description
Prediction of new data using rotationForest.
Function rotationForest [rotationForest v0.1.3]
keywords
classification
title
Binary classification with Rotation Forest (Rodriguez en Kuncheva, 2006)
description
rotationForest implements an ensemble method where each base classifier (tree) is fit on the principal components of the variables of random partitions of the feature set.
Function class_item [MultiLCIRT v2.11]
keywords
classification
title
Hierarchical classification of test items
description
It performs a hierarchical classification of a set of test items on the basis of the responses provided by a sample of subjects. The classification is based on a sequence of likelihood ratio tests between pairs of multidimensional models suitably formulated.
Function confusion [mixlm v1.2.4]
keywords
Classification
title
Confusion matrix.
description
Computes the confusion matrix of a classification result.
Function ex1data [bst v0.3-21]
keywords
classification
title
Generating Three-class Data with 50 Predictors
description
Randomly generate data for a three-class model.
Function rbst [bst v0.3-21]
keywords
classification
title
Robust Boosting for Robust Loss Functions
description
MM (majorization/minimization) algorithm based gradient boosting for optimizing nonconvex robust loss functions with componentwise linear, smoothing splines, tree models as base learners.
Function mhingebst [bst v0.3-21]
keywords
classification
title
Boosting for Multi-class Classification
description
Gradient boosting for optimizing multi-class hinge loss functions with componentwise linear least squares, smoothing splines and trees as base learners.
Function mhingeova [bst v0.3-21]
keywords
classification
title
Multi-class HingeBoost
description
Multi-class algorithm with one-vs-all binary HingeBoost which optimizes the hinge loss functions with componentwise linear, smoothing splines, tree models as base learners.
Function bst [bst v0.3-21]
keywords
classification
title
Boosting for Classification and Regression
description
Gradient boosting for optimizing loss functions with componentwise linear, smoothing splines, tree models as base learners.
Function mbst [bst v0.3-21]
keywords
classification
title
Boosting for Multi-Classification
description
Gradient boosting for optimizing multi-class loss functions with componentwise linear, smoothing splines, tree models as base learners.