Search Results for "decision tree c4.5 java"

Showing 12 open source projects for "decision tree c4.5 java"

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  • 1
    Toxtree: Toxic Hazard Estimation

    Toxtree: Toxic Hazard Estimation

    Toxicity prediction for chemical compounds

    ...Platform independent (written in Java), with the use of The Chemistry Development Kit.
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    Downloads: 209 This Week
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  • 2
    MYRA

    MYRA

    A collection of ACO algorithms for the data mining classification task

    MYRA is a collection of Ant Colony Optimization (ACO) algorithms for the data mining classification task. It includes popular rule induction and decision tree induction algorithms. The algorithms are ready to be used from the command line or can be easily called from your own Java code. They are build using a modular architecture, so they can be easily extended to incorporate different procedures and/or use different parameter values. This project is now hosted at: https://github.com/febo/myra
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    Downloads: 16 This Week
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  • 3
    Decision Tree

    Decision Tree

    ID3-based implementation of the ML Decision Tree algorithm

    DecisionTree is a Ruby library that implements decision tree learning with the ID3 information-gain algorithm. It can train models from discrete, continuous, or mixed attribute data. Continuous features are evaluated across possible split points to build threshold-based binary branches. Discrete models classify unique labels and can be rendered for visual inspection. The library supports inconsistent datasets, multiple or symbolic outputs, and fallback values when no branch matches an input....
    Downloads: 2 This Week
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  • 4

    Cost-sensitive Classifiers

    Adaboost extensions for cost-sentive classification

    Adaboost extensions for cost-sentive classification CSExtension 1 CSExtension 2 CSExtension 3 CSExtension 4 CSExtension 5 AdaCost Boost CostBoost Uboost CostUBoost AdaBoostM1 Implementation of all the listed algorithms of the cluster "cost-sensitive classification". They are the meta algorithms which requires base algorithms e.g. Decision Tree Moreover, Voting criteria is also required e.g. Minimum expected cost criteria Input also requires to load an arff file and a...
    Downloads: 0 This Week
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  • 5
    JBoost is a simple, robust system for classification. JBoost contains implementations of several boosting algorithms in an alternating decision tree framework. In addition, JBoost provides extensible software for adding more learning algorithms.
    Downloads: 1 This Week
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  • 6
    The DIDT (Distributed Id3-based Decision Tree) algorithm implementation in JAVA.
    Downloads: 0 This Week
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  • 7
    Interactive4J
    Project aim to provide simple easy APIs for Java developers to use interactive abilities in their Java Applications like speech recognition, handwriting recognition, use of web cam , sound record/play, decision trees , text to speech and many others.
    Downloads: 0 This Week
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  • 8
    Compiler of a 0+ order rule system. From a ruleset using attribute value formalism a decision tree is build and java/C/C++ execution code will be generated.
    Downloads: 4 This Week
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  • 9
    Avenzoar Digital Pathology Tool
    Avenzoar is a one-year exploration of renal cell carcinoma morphology and its related single nucleotide polymorphisms (SNPa) as a method of automating diagnosis of cancer by using a computer-aided decision tree controlled by analytical statistics.
    Downloads: 0 This Week
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  • 10
    Highly reusable and extensible Decision-Tree (Max-Gain) framework comprising of comprehensive input-processing and display functionality. Handles nominal, linear, continuous data. For preliminary description, refer - http://sushain.com/blog/archives/
    Downloads: 0 This Week
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  • 11
    The Decision Tree Learning algorithm ID3 extended with pre-pruning for WEKA, the free open-source Java API for Machine Learning. It achieves better accuracy than WEKA's ID3, which lacks pre-pruning.Info: http://bruno-wp.blogspot.com/search/label/Softwar
    Downloads: 0 This Week
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  • 12
    DTreeJungle provides educational applets to teach the concepts of decision trees for regular pattern recognition.
    Downloads: 0 This Week
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