OptimClassifier: Create the Best Train for Classification Models

Patterns searching and binary classification in economic and financial data is a large field of research. There are a large part of the data that the target variable is binary. Nowadays, many methodologies are used, this package collects most popular and compare different configuration options for Linear Models (LM), Generalized Linear Models (GLM), Linear Mixed Models (LMM), Discriminant Analysis (DA), Classification And Regression Trees (CART), Neural Networks (NN) and Support Vector Machines (SVM).

Version: 0.1.4
Depends: R (≥ 3.2.3)
Imports: crayon, dplyr, MASS, lme4, rpart, nnet, e1071, lmtest, nortest, clisymbols, ggplot2
Suggests: testthat, knitr, rmarkdown
Published: 2018-04-09
Author: Agustín Pérez-Martín ORCID iD [aut], Agustín Pérez-Torregrosa ORCID iD [cre, aut], Marta Vaca-Lamata ORCID iD [aut], Antonio José Verdú-Jover ORCID iD [aut]
Maintainer: Agustín Pérez-Torregrosa <agustin.perez01 at goumh.umh.es>
BugReports: https://github.com/economistgame/OptimClassifier/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://economistgame.github.io/OptimClassifier
NeedsCompilation: no
Materials: README NEWS
CRAN checks: OptimClassifier results

Downloads:

Reference manual: OptimClassifier.pdf
Vignettes: An Introduction to OptimClassifier
Package source: OptimClassifier_0.1.4.tar.gz
Windows binaries: r-devel: OptimClassifier_0.1.4.zip, r-release: OptimClassifier_0.1.4.zip, r-oldrel: OptimClassifier_0.1.4.zip
OS X binaries: r-release: OptimClassifier_0.1.4.tgz, r-oldrel: OptimClassifier_0.1.4.tgz
Old sources: OptimClassifier archive

Reverse dependencies:

Reverse depends: RcmdrPlugin.OptimClassifier

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