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        "author": "Anders Bogsnes",
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        "description": "# Model Tooling library\n[![Build Status](https://github.com/andersbogsnes/ml_tooling/workflows/Tests/badge.svg)](https://github.com/andersbogsnes/ml_tooling/actions?workflow=Tests)\n[![codecov](https://codecov.io/gh/andersbogsnes/ml_tooling/branch/develop/graph/badge.svg)](https://codecov.io/gh/andersbogsnes/ml_tooling)\n[![Python 3](https://img.shields.io/pypi/pyversions/ml_tooling.svg)](https://pyup.io/repos/github/andersbogsnes/ml_tooling/)\n[![CodeFactor](https://www.codefactor.io/repository/github/andersbogsnes/ml_tooling/badge)](https://www.codefactor.io/repository/github/andersbogsnes/ml_tooling)\n[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)\n\n## Installation\nUse pip to install:\n`pip install ml-tooling`\nOr use conda\n`conda install -c conda-forge ml_tooling`\n\n## Test\nWe use `tox` for managing build and test environments, to install `tox` run:\n`pip install tox`\nAnd to run tests:\n`tox -e py`\n\n## Example usage\nDefine a class using ModelData and implement the two required methods.\nHere we simply implement a linear regression on the Boston dataset using sklearn.datasets\n```python\nfrom sklearn.datasets import load_boston\nfrom sklearn.linear_model import LinearRegression\n\nfrom ml_tooling import Model\nfrom ml_tooling.data import Dataset\n\n# Define a new data class\nclass BostonData(Dataset):\n    def load_prediction_data(self, idx):\n        x, _ = load_boston(return_X_y=True)\n        return x[idx] # Return given observation\n\n    def load_training_data(self):\n        return load_boston(return_X_y=True)\n\n# Instantiate a model with an estimator\nlinear_boston = Model(LinearRegression())\n\n# Instantiate the data\ndata = BostonData()\n\n# Split training and test data\ndata.create_train_test()\n\n# Score the estimator yielding a Result object\nresult = linear_boston.score_estimator(data)\n\n# Visualize the result\nresult.plot.prediction_error()\n\nprint(result)\n<Result LinearRegression: {'r2': 0.68}>\n```\n\n\n## Links\n* Documentation: https://ml-tooling.readthedocs.io\n* Releases: https://pypi.org/project/ml_tooling/\n* Code: https://github.com/andersbogsnes/ml_tooling\n* Issue Tracker: https://github.com/andersbogsnes/ml_tooling/issues\n\n\n",
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