Showing 15 open source projects for "data mining"

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  • 1
    GFP- GAKNN
    GAKNN is a data mining software for gene annotation data. GAKNN is built with k- Nearest Neighbour algorithm optimized by the genetic algorithm. Gene annotation datasets saved under .csv or .arff formats with Gene Ontology or FunCat categorization can use GAKNN to predict gene functions.
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  • 2

    Algorithm Database

    Efficient Algorithms implemented in Java

    ...Objective here is to implement algorithms which should be more efficient than the JDK implementation and also to create a platform for the researchers who works on Data Mining, Encryption algorithms, ect.. to collaborate and contribute to this project.
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  • 3
    Mr.FSM

    Mr.FSM

    Large-Scale Frequent Subgraph Mining in MapReduce

    This is the program used in the following paper: Wenqing Lin, Xiaokui Xiao, and Gabriel Ghinita. Large-Scale Frequent Subgraph Mining in MapReduce. In Proceedings of the 30th IEEE International Conference on Data Engineering (ICDE), pages 844-855, 2014. Please cite the paper if you choose to use the program. If having any problems, please report to {wlin1 at ntu dot edu dot sg}.
    Downloads: 0 This Week
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  • 4
    MRA

    MRA

    A general recommender system with basic models and MRA

    Multi-categorization Recommendation Adjusting (MRA) is to optimize the results of recommendation based on traditional(basic) recommendation models, through introducing objective category information and taking use of the feature that users always get the habits of preferring certain categories. Besides this, there are two advantages of this improved model: 1) it can be easily applied to any kind of existing recommendation models. And 2) a controller is set in this improved model to provide...
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  • 5
    Math tools in Python to tackle down problems in Operational Research fields. Comes with a Django based web interface to allow remote access to complex simulation means.
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  • 6
    Genetic Programming (tree structure) predictor within Weka data mining software for both continuous and classification problems.
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  • 7
    Openminer, as a data mining engine, is developed on java for analysis of dataset with the methods of data mining. By making use of openminer, we could discovery the knowledge which interests us but hides in the raw data.
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  • 8
    Library Of Randomized Algorithms: Randomization is a powerful idea has applications in science and engineering. Difficult optimization problems, protein folding and data mining are only a few of the problems that have been solved using randomization.
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  • 9
    KNN-WEKA provides a implementation of the K-nearest neighbour algorithm for Weka. Weka is a collection of machine learning algorithms for data mining tasks. For more information on Weka, see http://www.cs.waikato.ac.nz/ml/weka/.
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  • 10
    NOD-MP stands for not another data-mining project. It is educational and scientific software to utilize data mining clustering algorithms through a user-friendly interface.
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  • 11
    DMTL (Data Mining Template Library) - A generic C++ based library for mining structured patterns such as sets, sequences, trees and graphs. The library provides implementation of popular frequent pattern mining algorithms.
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  • 12
    This project intends to create an indexing search engine, for knowledge management. The primary object is to apply an information retrieval core. And implement a knowledge data discovery theory such as data mining algorithm, text mining.
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  • 13
    musicomp is a program which most important element is an evolutionary algorithm which uses data mining methods as a fitness function to generate monophone melodies.
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  • 14
    Centre is a synthetic trajectory generator environment that aim to generate semantic-based trajectory datasets usable for spatio-temporal data-mining algorithms in testing and validation process.
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  • 15
    Weka++ is a collection of machine learning and data mining algorithm implementations ported from Weka (http://www.cs.waikato.ac.nz/ml/weka/) from Java to C++, with enhancements for usability as embedded components.
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