Metadata-Version: 1.1
Name: prediction_evaluation
Version: 0.0.0
Summary: evaluation of prediction of binary, multiclass and regression
Home-page: https://github.com/MandyZhangxy/DATS6450-final-project.git
Author: Xinyu Zhang, Yijia Chen, Xiaochi Ge
Author-email: mandy_zhang512@gwu.edu
License: GNU
Description-Content-Type: UNKNOWN
Description: # DATS6450-final-project
        ---
        
        This package is visualization for evaluation of prediction and performances of machine learning models based on the target variables and models' prediction.
        There are three types of model prediction:
        
        * Binary classification Evaluation
        * Multiclass classification Evaluation
        * Regression Evaluation
        
        ## Installation
        
        You can install `prediction_evaluation` with `pip`:
        
        `# pip install prediction_evaluation `
        
        ## The models:
        ---
        
        ### 1. Binary classification
        * Confusion matrix plot
        * ROC score and AUC plot
        * Precision, recall and f1-score score table
        
        ### 2. Multi-class classification
        * Confusion Matrix
        * ROC score and AUC plot
        * Precision, recall and f1-score score table
        
        ### 3. Regression
        * Mean absolute error (MAE)
        * Mean Squared error (MSE)
        * R^2 score
        * Residual plot
        
        <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>.
        
Keywords: binary classification,regression,multiclass,evaluation
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 2
