coffee

<p>A dataset containing 56 times series z-normalized. Time series length is 286.</p>

datasets

Provides a collection of self-labeled techniques for semi-supervised
classification. In semi-supervised classification, both labeled and unlabeled
data are used to train a classifier. This learning paradigm has obtained promising
results, specifically in the presence of a reduced set of labeled examples.
This package implements a collection of self-labeled techniques to construct a
classification model. This family of techniques enlarges the original labeled set
using the most confident predictions to classify unlabeled data. The techniques
implemented can be applied to classification problems in several domains by the
specification of a supervised base classifier. At low ratios of labeled data, it
can be shown to perform better than classical supervised classifiers.

Christoph Bergmeir

Semi-Supervised Classification Methods

Mabel Gonz<c3><a1>lez

Osmani Rosado-Falc<c3><b3>n

Jos<c3><a9> Daniel Rodr<c3><ad>guez

Isaac Triguero

Jos<c3><a9> Manuel Ben<c3><ad>tez

coffee function

<p>A data frame with 56 rows and 287 variables including the class.</p>

Format

Time series data set — coffee

Time series data set

coffee: Time series data set

Description

Usage

Arguments

Format