Showing 1661 open source projects for "machine learning platform"

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  • 1
    Linear Time Invariant (LTI) system identification using particle swarm optimization (PSO) algorithm. Creators : Vahid Kiani, Hadi Sadoghi Yazdi
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  • 2
    Aleph is both a multi-platform machine learning framework aimed at simplicity and performance, and a library of selected state-of-the-art algorithms.
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  • 3
    A packet dissector driven by machine learning algorithms. You train it to recognize specific types of packets by showing it examples and counterexamples of some packet type, and it will figure out which bits in the packet define it as the type you seek.
    Downloads: 0 This Week
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  • 4
    TrimGA is a lightweight genetic algorithm library written in pure Java 6.0 that can be quickly applied to most optimization problems.
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  • 5
    A C++ library for machine learning within dynamic systems. It provides methods such as the Kalman, unscented Kalman, and particle filters and smoothers, as well as useful classes such as common probability distributions and stochastic processes.
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  • 6
    This project is developing a modular framework for constructing machine intelligences. The modular approach allows for both rapid development of simple AI's and also construction of larger and more general learning based engines.
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  • 7
    Structlab is a machine learning C++ framework for structured domains, which provides a toolbox of learning methods and tools for preprocessing and visualization. It also provides a GUI to setup elaborate experiments in a visual and intuitive way.
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  • 8
    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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  • 9
    T-Rex (Trainable Relation Extraction) is a highly configurable machine learning-based Information Extraction from Text framework, which includes tools for document classification, entity extraction and relation extraction.
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  • 10

    TimeSleuth - Temporal Rule Discovery

    Temporal and Causal Decision Rules

    TimeSleuth discovers temporal decision rules. It also judges the (a)causality of the rules. TimeSleuth can discover rules that involve time: {if (rainy_yesterday = true) then rainy_today = true}, or {if (rainy_tomorrow = true) then rainy_today = true}.
    Downloads: 0 This Week
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  • 11
    COLDIC is an integrated lexicographic platform for creation and management of electronic lexica. Generates itself automatically from a DTD with the database schema and provides human interfaces (query and insert tools) and machine interfaces(webservices)
    Downloads: 0 This Week
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  • 12
    Cerberus is a First Person Shooter Game that incorporates machine learning techniques. The game utilizes Neural Networks to control fighting behavior and Reinforcement Learning to select high level tactics.
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  • 13
    The Free Connectionist Q-learning Java Framework is an library for developing learning systems. Keywords: qlearning, artificial intelligence, alife, neural nets, neural networks, machine learning, reinforcement learning unsupervised learning agents lejos
    Downloads: 0 This Week
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  • 14
    The simpleSVM project contains Machine Learning codes for algorithms based on the SimpleSVM. It provides methods for Support Vector Machines and related methods, such as One-Clas SVM, nu-SVM...
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    Downloads: 23 This Week
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  • 15
    PIQLE is a Platform Implementing Q-LEarning (and other Reinforcement Learning) algorithms in JAVA. Version 2 is a major refactoring. The core data structures and algorithms are in piqle-coreVersion2. Examples are in piqle-examplesVersion2. A complete doc
    Downloads: 0 This Week
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  • 16
    Zabal6 is a machine learning student tool based on decision tree learning, focused in the area of knowledge discovery (data mining), and inspired on See5. Zabl6 is a C++ program for Linux and windows O.S, with a intuitive graphical interface.
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  • 17
    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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  • 18
    A discretization algorithm based on the Minimum Description Length. Implemented as a filter according to the standards and interfaces of WEKA, the Java API for Machine Learning. More Info: http://bruno-wp.blogspot.com/search/label/Software
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  • 19
    Machine learning toolkit for unsupervised and semi-supervised clustering that demonstrates excellent results on real-world data (see Bekkerman et al. ICML-2005 and ECML-2006).
    Downloads: 0 This Week
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  • 20
    Conrad is both a high performance Conditional Random Field engine which can be applied to a variety of machine learning problems and a specific set of models for gene prediction using semi-Markov CRFs.
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  • 21
    A tool for segmenting objects of interest in images, namely creating masks, and storing them for a set of images. It may provide some automatic/interactive segmentation for certain classes of objects. For computer vision / machine learning applications.
    Downloads: 0 This Week
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  • 22
    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/.
    Downloads: 0 This Week
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  • 23
    PCP (Pattern Classification Program) is an open-source machine learning program for supervised classification of patterns. PCP is a binary executable running on Linux and Windows (under Cygwin environment).
    Downloads: 1 This Week
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  • 24
    An object-oriented platform and algorithms for the game of GO. Aims: 1) A capable engine that can learn through experience. 2) A re-usable algorithmic framework for rapid development of new GO-playing engines.
    Downloads: 0 This Week
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  • 25
    MultiBoost is a C++ implementation of the multi-class AdaBoost algorithm. AdaBoost is a powerful meta-learning algorithm commonly used in machine learning. The code is well documented and easy to extend, especially for adding new weak learners.
    Downloads: 2 This Week
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