Showing 3 open source projects for "numeric"

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    Stanford CoreNLP

    Stanford CoreNLP

    Stanford CoreNLP, a Java suite of core NLP tools

    CoreNLP is your one stop shop for natural language processing in Java! CoreNLP enables users to derive linguistic annotations for text, including token and sentence boundaries, parts of speech, named entities, numeric and time values, dependency and constituency parses, coreference, sentiment, quote attributions, and relations. CoreNLP currently supports 6 languages, Arabic, Chinese, English, French, German, and Spanish. The centerpiece of CoreNLP is the pipeline. Pipelines take in raw text, run a series of NLP annotators on the text, and produce a final set of annotations. ...
    Downloads: 1 This Week
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  • 2
    MODLEM

    MODLEM

    rule-based, WEKA compatible, Machine Learning algorithm

    This project is a WEKA (Waikato Environment for Knowledge Analysis) compatible implementation of MODLEM - a Machine Learning algorithm which induces minimum set of rules. These rules can be adopted as a classifier (in terms of ML). It is a sequential covering algorithm, which was invented to cope with numeric data without discretization. Actually the nominal and numeric attributes are treated in the same way: attribute's space is being searched to find the best rule condition during rule induction. In result numeric attribute's conditions are more precise and closely describe the class. This algorithm contains some aspects of Rough Set Theory: the class definition can be described accordingly to its lower or upper approximation. ...
    Downloads: 17 This Week
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  • 3
    Application of neural network to predict the future of stock exchange, aerospace ( ufo trajectory ), sound, image, noise, scientific or medical data. You need , by example, 100 days of a numeric data and the number of days to predict (by example 7 days).
    Downloads: 0 This Week
    Last Update:
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