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        "author": "Xinyu Zhang, Yijia Chen, Xiaochi Ge",
        "author_email": "mandy_zhang512@gwu.edu",
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        "description": "# DATS6450-final-project\n---\n\nThis package is visualization for evaluation of prediction and performances of machine learning models based on the target variables and models' prediction.\nThere are three types of model prediction:\n\n* Binary classification Evaluation\n* Multiclass classification Evaluation\n* Regression Evaluation\n\n## Installation\n\nYou can install `prediction_evaluation` with `pip`:\n\n`# pip install prediction_evaluation `\n\n## The models:\n---\n\n### 1. Binary classification\n* Confusion matrix plot\n* ROC score and AUC plot\n* Precision, recall and f1-score score table\n\n### 2. Multi-class classification\n* Confusion Matrix\n* ROC score and AUC plot\n* Precision, recall and f1-score score table\n\n### 3. Regression\n* Mean absolute error (MAE)\n* Mean Squared error (MSE)\n* R^2 score\n* Residual plot\n\n<a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc/4.0/\"><img alt=\"Creative Commons License\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by-nc/4.0/88x31.png\" /></a><br />This work is licensed under a <a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc/4.0/\">Creative Commons Attribution-NonCommercial 4.0 International License</a>.",
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