Showing 4 open source projects for "options"

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    Build Agents and Models on One Platform

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  • 1
    YAPF

    YAPF

    A formatter for Python files

    ...You can run it as a command-line tool or call it as a library via FormatCode / FormatFile, making it easy to embed in editors, CI, and custom tooling. Styles are highly configurable: start from presets like pep8, google, yapf, or facebook, then override dozens of options in .style.yapf, setup.cfg, or pyproject.toml. It supports recursive directory formatting, line-range formatting, and diff-only output so you can check or fix just the lines you touched.
    Downloads: 5 This Week
    Last Update:
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  • 2
    Active Learning

    Active Learning

    Framework and examples for active learning with machine learning model

    ...The main experiment runner (run_experiment.py) supports a wide range of configurations, including batch sizes, dataset subsets, model selection, and data preprocessing options. It includes several established active learning strategies such as uncertainty sampling, k-center greedy selection, and bandit-based methods, while also allowing for custom algorithm implementations. The framework integrates with both classical machine learning models (SVM, logistic regression) and neural networks.
    Downloads: 1 This Week
    Last Update:
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  • 3

    ProximityForest

    Efficient Approximate Nearest Neighbors for General Metric Spaces

    ...This source code is provided without warranty and is available under the GPL license. More commercially-friendly licenses may be available. Please contact Stephen O'Hara for license options. Please view the wiki on this site for installation instructions and examples on reproducing the results of the papers.
    Downloads: 0 This Week
    Last Update:
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  • 4
    The optex module for Python 2.4 helps user scripts to parse command line arguments found in sys.argv. Options are parsed in a different manner than the Unix getopt() and Python getopt module.
    Downloads: 0 This Week
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    Build Securely on Azure with Proven Frameworks

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