EvaluateClusteredLinearMTModel: Evaluate clustered LinearMTL model.

In tohein/linearMTL: Linear Models for Multi-Task Learning

Description

Compute training and test errors for the given indices.

Usage

EvaluateClusteredLinearMTModel(X = NULL, task.specific.features = list(), Y,
  LMTL.model.list, train.idx.by.cluster, test.idx.by.cluster,
  task.names = NULL, out.dir)

Arguments

X	Column centered N by J input matrix of features common to all tasks.
task.specific.features	Named list of features which are specific to each task. Each entry contains an N by J2 column-centered matrix for one particular task (where columns are features). List has to be ordered according to the columns of Y.
Y	Column centered N by K output matrix for every task.
LMTL.model.list	List of LinearMTL models.
train.idx.by.cluster	List of training indices per cluster.
test.idx.by.cluster	List of test indices per cluster.
task.names	Task names.
out.dir	Output directory for results and plots.

tohein/linearMTL documentation built on May 17, 2019, 8:22 a.m.