Search Results for "project weka"
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Showing 15 open source projects for "project weka"
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MOA - Massive Online Analysis
Big Data Stream Analytics Framework.
A framework for learning from a continuous supply of examples, a data stream. Includes classification, regression, clustering, outlier detection and recommender systems. Related to the WEKA project, also written in Java, while scaling to adaptive large scale machine learning. -
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ADAMS
ADAMS is a workflow engine for building complex knowledge workflows.
ADAMS is a flexible workflow engine aimed at quickly building and maintaining data-driven, reactive workflows, easily integrated into business processes. Instead of placing operators on a canvas and manually connecting them, a tree structure and flow control operators determine how data is processed (sequentially/parallel). This allows rapid development and easy maintenance of large workflows, with hundreds or thousands of operators. Operators include machine learning (WEKA, MOA, MEKA... -
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JCLALtext
Text processing module for JCLAL
JCLALtext is a class library designed to extend the framework JCLAL text tasks. JCLALtext is free, open source and developed with the Java programming language. JCLALtext is distributed under the GNU license. The researcher can use the class library by adding it to your project. -
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MODLEM
rule-based, WEKA compatible, Machine Learning algorithm
This project is a WEKA (Waikato Environment for Knowledge Analysis) compatible implementation of MODLEM - a Machine Learning algorithm which induces minimum set of rules. These rules can be adopted as a classifier (in terms of ML). It is a sequential covering algorithm, which was invented to cope with numeric data without discretization. Actually the nominal and numeric attributes are treated in the same way: attribute's space is being searched to find the best rule condition during rule... -
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Mechaglot, Calculate Semantic Similarity
Calculate semantic similarity for any human and human-like languages
... is, this project does not use any database and computes any Strings as an input. JAVA was the language of choice, due to availability of modelling tools. This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-sa/4.0/. -Powered by WEKA, Classifier4J and SimMetrics. -
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Multilabel Dataset GUI
An application for evaluating metric in Multilabel dataset
Multilabel Dataset GUI is a software for evaluating metric in Multilabel dataset. In this project we try to collect as much information as possible for characterizing multilabel dataset. This application is closely based upon the Weka and MULAN framework. -
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feed4weka is an open library that enriches weka (http://www.cs.waikato.ac.nz/ml/weka/), an open source project for data analysis. It integrates new classification and clustering algorithms, and adds the coclustering and outlier detection frameworks
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This project contains weka packages of neural networks algorithms implementations like Learning Vector Quantizer (LVQ) and Self-organizing Maps (SOM). For more information about weka, please visit http://www.cs.waikato.ac.nz/~ml/weka/
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stocleka is a project divided into a UI and a library for cleaning user stories and converting them to arff files (used for Weka). it may be mainly used for research and scientific purposes.
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PDMGE is a software developed for predicting CpG loci and genomic region methylation status. The software is based on Weka project,which extends WEKA to promoter the development of epigenetics. Users should prepare genomic and epigenomic features.
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Dataset Retrieval through Intelligent Agents (DARIA): is an Open Source project for facilitating the construction of ARFF data set files for use with WEKA or any such Machine Learning/Data Mining Software through the use of Intelligent Agents.
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The aim of the BioWeka project is to add bioinformatics functionalities such as e.g. alignments to the popular machine learning framework Weka.
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MLP is a library containing a framework for the development of Machine Learning algorithms as well as a set of standard ML algorithms ready to be used. It is similar in the spirit to the weka project, but it is written in C++.
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Software Weka-ERP is based on software WEKA - http://www.cs.waikato.ac.nz/~ml/weka/ . This project extends the current version of WEKA software and integration of this software with tools for EEG/ERP data processing.
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