EnglishFrenchSpanish

Ad


OnWorks favicon

GA-EoC to run in Linux online download for Linux

Free download GA-EoC to run in Linux online Linux app to run online in Ubuntu online, Fedora online or Debian online

This is the Linux app named GA-EoC to run in Linux online whose latest release can be downloaded as GA-EoC.jar. It can be run online in the free hosting provider OnWorks for workstations.

Download and run online this app named GA-EoC to run in Linux online with OnWorks for free.

Follow these instructions in order to run this app:

- 1. Downloaded this application in your PC.

- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.

- 3. Upload this application in such filemanager.

- 4. Start the OnWorks Linux online or Windows online emulator or MACOS online emulator from this website.

- 5. From the OnWorks Linux OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.

- 6. Download the application, install it and run it.

SCREENSHOTS

Ad


GA-EoC to run in Linux online


DESCRIPTION

In data classification, there are no particular classifiers that perform consistently in every case. This is even worst in case of both the high dimensional and class-imbalanced datasets.

To overcome the limitations of class-imbalanced data, we split the dataset using a random sub-sampling to balance them. Then, we apply the (alpha,beta)-k feature set method to select a better subset of features and combine their outputs to get a consolidated feature set for classifier training.

To enhance classification performances, we propose an ensemble of classifiers that combine the classification outputs of base classifiers using the simplest and largely used majority voting approach.

Instead of creating the ensemble using all base classifiers, we have implemented a genetic algorithm (GA) to search for the best combination from heterogeneous base classifiers.

The classification performances achieved by the proposed method method on the chosen datasets are promising.

Features

  • Generate Cross Validation folds and save datasets into disk for future usage in ARFF format
  • Generate and serialize into disk of Classifier Models for all cross validation Training Folds for use by GA-EoC
  • Generate and serialize into disk of All Base Classifier Models using the Full Training dataset.
  • Search for best ensemble combinations to create heterogeneous ensemble of classifiers using k-fold cross validation on training dataset (using pre-generated CV dataset and models)
  • Evaluate the performance of best ensemble combination on unknown Testing Data (use pre-generated models using full training data)


Audience

Information Technology, Science/Research, Education, Advanced End Users, Developers


User interface

Console/Terminal, Command-line


Programming Language

Java



This is an application that can also be fetched from https://sourceforge.net/projects/geneticensembleclassifier/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.


Free Servers & Workstations

Download Windows & Linux apps

Linux commands

Ad