Showing 58 open source projects for "classification"

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  • 1
    The Word Vector Tool is a simple but flexible Java library to create word vector representations of text documents. Word vectors can be used for various text processing tasks, as text classification, text clustering or information retrieval.
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  • 2
    Random Forest classification implementation in Java based on Breiman's algorithm (2001). It assumes the data is in the form [ X_1, X_2, . . ., X_M, Y ] where Y \in {0, 1, . . ., C}. The user must define M, C, and m initially.
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  • 3
    Qualiweb aims at providing semantic web metrics for modeling a website visitors needs according to a given taxonomy or document classification. Web metrics provided by Qualiweb give an indication of how successful each of the website topics have been.
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  • 4
    Naive-Bayes based classification services for Avalon/Keel framework IOC containers.
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  • 5
    Pattern recognition software package. It includes several classification and clustering algorithms. It can read data from a set of images, an ASCII file or a JDBC connection. A small TCP data server with its corresponding JDBC driver is included.
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  • 6
    Librarian is intelligent text classification system. That provide you with the access to your electronic document based on a hierarchical system of classifications.
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  • 7

    Cinefile

    A category-based approach to exploring film data.

    ...It allows the user to identify abstract categories of films by providing examples of category members, learns to classify films as belonging or not belonging to those categories, and provides a graphical interface for exploring and comparing categories. Cinefile is designed to work with data retrieved from the Internet Movie Database (imdb.com). This data is used for classification and is the subject of the category-based analysis. Cinefile was developed by the University of Mary Washington's Computer Science department (http://cas.umw.edu/computerscience).
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  • 8
    Data Mining Platform is a platform for data mining and analysis. It contains many of the new and sophisticated methods such as kernel-based classification, two-way clustering, bayesian networks, pattern recognition for time series analysis and many other
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