CRAN

OptimClassifier 0.1.4

Create the Best Train for Classification Models

Released Apr 9, 2018 by Agustín Pérez-Torregrosa

This package is available for Renjin and there are no known compatibility issues.

Dependencies

crayon 1.3.4 ggplot2 2.2.1 MASS 7.3-49 nnet 7.3-12 clisymbols 1.2.0 lme4 1.1-17 lmtest 0.9-36 nortest 1.0-4 rpart 4.1-13 e1071 1.6-8 dplyr 0.7.4

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).

Installation

Maven

This package can be included as a dependency from a Java or Scala project by including the following your project's pom.xml file. Read more about embedding Renjin in JVM-based projects.

<dependencies>
  <dependency>
    <groupId>org.renjin.cran</groupId>
    <artifactId>OptimClassifier</artifactId>
    <version>0.1.4-b1</version>
  </dependency>
</dependencies>
<repositories>
  <repository>
    <id>bedatadriven</id>
    <name>bedatadriven public repo</name>
    <url>https://nexus.bedatadriven.com/content/groups/public/</url>
  </repository>
</repositories>

View build log

Renjin CLI

If you're using Renjin from the command line, you load this library by invoking:

library('org.renjin.cran:OptimClassifier')

Test Results

This package was last tested against Renjin 0.9.2635 on Apr 26, 2018.

Source

R

View GitHub Mirror

Release History