Showing 66 open source projects for "machine learning platform"

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  • 1
    MyNook

    MyNook

    A machine learning system for supervised document classification

    An open source system for supervised document classification based on statistical machine learning techniques. On the contrary of the state of art classification techniques, MyNook just requires the title of the document, not the content itself.
    Downloads: 0 This Week
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  • 2

    ABC-DynF

    Adaptive Bayesian Classifier with Dynamic Features

    Downloads: 0 This Week
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  • 3

    AdPreqFr4SL

    Adaptive Prequential Learning Framework

    The AdPreqFr4SL learning framework for Bayesian Network Classifiers is designed to handle the cost / performance trade-off and cope with concept drift. Our strategy for incorporating new data is based on bias management and gradual adaptation. Starting with the simple Naive Bayes, we scale up the complexity by gradually updating attributes and structure. Since updating the structure is a costly task, we use new data to primarily adapt the parameters and only if this is really necessary, do we...
    Downloads: 0 This Week
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  • 4
    This is a Matlab software package for single molecule FRET data analysis.
    Downloads: 1 This Week
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  • 5
    CRFSharp

    CRFSharp

    CRFSharp is a .NET(C#) implementation of Conditional Random Field

    CRFSharp(aka CRF#) is a .NET(C#) implementation of Conditional Random Fields, an machine learning algorithm for learning from labeled sequences of examples. It is widely used in Natural Language Process (NLP) tasks, for example: word breaker, postagging, named entity recognized, query chunking and so on. CRF#'s mainly algorithm is the same as CRF++ written by Taku Kudo. It encodes model parameters by L-BFGS. Moreover, it has many significant improvement than CRF++, such as totally parallel encoding, optimizing memory usage and so on. ...
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  • 6
    Proper is a propositionalization framework written in Java containing several algorithms for generating propositional (and also multi-instance) data from relational databases. It produces data that can be used by the WEKA machine learning workbench.
    Downloads: 4 This Week
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  • 7
    This is a variant of k-means algorithm which allows datas to belong to several clusters instead of just one.
    Downloads: 0 This Week
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  • 8
    SVM# is a svm(support vector machine) classification implemented in C#. The project contains both train and predict modules.
    Downloads: 0 This Week
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  • 9
    A Machine Learning and Data Retrieval Framework
    Downloads: 0 This Week
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  • 10
    Cougar Squared is a new Java library for machine learning and data mining research, supporting research needs of the community. It is written by researchers for researchers. It extends the WEKA and YALE machine learning frameworks.
    Downloads: 0 This Week
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  • 11
    Feating constructs a classification ensemble comprising a set of local models. It is effective at reducing the error of both stable and unstable learners, including SVM. For details see the paper at http://dx.doi.org/10.1007/s10994-010-5224-5.
    Downloads: 0 This Week
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  • 12
    Content Addressable Memory, Multi-Variate Statistics, Data Mining Includes analyzing datasets, extracting patterns, creating empirical expert system. Computes joint probabilities and implements a "belief" as the solution of an equilibrium equation
    Downloads: 0 This Week
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  • 13
    MLboost: Machine Learning boost library in Python. MLboost main goal is to speedup any Machine Learning projects by simplifying data preprocessing, features selection and data visualisation. Design by Machine Learning practitioners to let them do ML...;)
    Downloads: 0 This Week
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  • 14
    Monte is machine learning in pure Python. Monte's focus is the construction of gradient based learning machines from many small components.
    Downloads: 0 This Week
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  • 15
    Optex Analyzer is a software to analyze and compare algorithms to solve approximately optimization problems. It has a GUI that allows select a set of input files containing raw algorithm results. The analysis is shown with tables and charts.
    Downloads: 0 This Week
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  • 16
    A java tool for anytime and interactive sequence mining. Aims at providing users with a way of analyzing her activity traces and extract activity schemes from them.
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  • 17
    Platform supporting machine learning on different objects by different modification of the JSM method (for now). Predicates for the JSM method are written in CLIPS.Objects and modification of the JSM method have to written on one of .NET languages.
    Downloads: 0 This Week
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  • 18
    Maui is a multi-purpose automatic topic indexing algorithm. Given a document, Maui automatically identifies its topics. Depending on the task topics are tags, keywords, keyphrases, vocabulary terms, descriptors or Wikipedia titles.
    Downloads: 0 This Week
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  • 19
    Multiclass machine learning
    Downloads: 0 This Week
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  • 20
    A Python function library to extract EEG feature from EEG time series in standard Python and numpy data structure. Features include classical spectral analysis, entropies, fractal dimensions, DFA, inter-channel synchrony and order, etc.
    Downloads: 0 This Week
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  • 21
    Blunder is an automated tool for analyzing chained exceptions in Java. It's usefull for classify, generate a customized error message and a list for possible solutions.
    Downloads: 0 This Week
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  • 22
    Taste
    Now part of Apache's Mahout machine learning project at http://mahout.apache.org/-- please see there for latest info and code and releases and support!
    Downloads: 0 This Week
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  • 23
    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.
    Downloads: 0 This Week
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  • 24
    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.
    Downloads: 0 This Week
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  • 25

    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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