Name | Modified | Size | Downloads / Week |
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IPR_GUI_fuge_mlp_v1.1 | 2014-10-16 | ||
README.txt | 2014-10-22 | 2.9 kB | |
LICENSE.txt | 2014-10-15 | 35.1 kB | |
Totals: 3 Items | 38.1 kB | 0 |
# An application to create models and make predictions from existing models for FugeR and monmlp # Author = Hassan Khalid, Project = IPROCOM, # Date = 15-10-2014, Krakow, PL # Co-Authors: # Aleksander Mendyk: mfmendyk@cyf-kr.edu.pl; aleksander.mendyk@uj.edu.pl # Adam Pacławski: adam.paclawski@uj.edu.pl # Jakub Szlęk: j.szlek@uj.edu.pl # License: GPLv3 # This program comes with ABSOLUTELY NO WARRANTY! USE IT AT YOR OWN RISK! # Acknowledgment: This work was supported by the IPROCOM Marie Curie initial training network, funded through the People Programme (Marie Curie Actions) of the European # Union’s Seventh Framework Programme FP7/2007-2013/ under REA grant agreement No. 316555. # version: 1.1 This App creates models and make predictions from existing models for FugeR and monmlp monmlp is a Neural Network-based data analysis system. For more information please refer to its original manual at the CRAN repostitory: http://cran.r-project.org/web/packages/monmlp/index.html fugeR is "an evolutionary algorithm for fuzzy systems, a genetic algorithm is used to construct a fuzzy system able to fit the given training data. This fuzzy system can then be used as a prediction model, it's composed of fuzzy logic rules that provide a good lingustic representation." http://cran.r-project.org/web/packages/fugeR/index.html It requires data prepared in a manner of 1 pair of training-testing datasets in TXT files, where the last column contains the known answer to the problem (dependent variable) and previous columns are features (regressors or independent variables). The assumption is that the model is of MISO type (multiple-input-single-output) Output shows a predicted vs observed graph with an abline. **Please keep all data and object files in the same directory as your app and set it as your working directory for smooth running of the app. To execute: Download the ui.R and server.R files, and the www folder in to one directory. When running for the first time, Please copy and run the following code on R studio: install.packages("shiny", "monmlp", "devtools", "fugeR") library(devtools) install_github("shiny-incubator", "rstudio") library(shiny) library(monmlp) library(shinyIncubator) library(fugeR) For an illustrative example, one training-test file pair has been provided. Please find an example of how to run the script in the example.tar.gz archive Runs on Linux and Mac Windows users must get rid of multicore library ########################################################################## This program comes with ABSOLUTELY NO WARRANTY This is free software, and you are welcome to redistribute it under certain conditions. Please find a LICENSE file to look for a more detailed description of terms and conditions based on the GNU GPLv3 license ##########################################################################