| 1 | # -*- coding: utf-8; mode: tcl; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- vim:fenc=utf-8:ft=tcl:et:sw=4:ts=4:sts=4 |
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| 2 | # $Id$ |
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| 3 | |
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| 4 | PortSystem 1.0 |
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| 5 | PortGroup python27 1.0 |
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| 6 | |
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| 7 | name py27-mlpy |
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| 8 | version 2.2.2 |
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| 9 | revision 1 |
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| 10 | categories lang python |
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| 11 | maintainers gmail.com:marc.schlaich |
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| 12 | description Python package for predictive modeling |
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| 13 | long_description \ |
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| 14 | mlpy is a high-performance Python package for predictive modeling. \ |
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| 15 | It makes extensive use of NumPy (http://scipy.org) to provide fast \ |
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| 16 | N-dimensional array manipulation and easy integration of C code. mlpy \ |
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| 17 | provides high level procedures that support, with few lines of code, \ |
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| 18 | the design of rich Data Analysis Protocols (DAPs) for preprocessing, \ |
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| 19 | clustering, predictive classification and feature selection. Methods \ |
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| 20 | are available for feature weighting and ranking, data resampling, \ |
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| 21 | error evaluation and experiment landscaping. The package includes \ |
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| 22 | tools to measure stability in sets of ranked feature lists. |
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| 23 | |
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| 24 | platforms darwin |
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| 25 | |
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| 26 | homepage https://mlpy.fbk.eu/ |
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| 27 | master_sites https://mlpy.fbk.eu/download/src/ \ |
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| 28 | |
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| 29 | distname MLPY-${version} |
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| 30 | |
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| 31 | checksums sha1 6783f96f28d31adac65c8135631231f2bc1e0210 \ |
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| 32 | rmd160 80d37e3ebb0c23c5d6a329721c526c4c18a74aac |
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| 33 | |
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| 34 | depends_lib port:gsl port:py27-cython |
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| 35 | depends_build port:py27-distribute |
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