Metadata-Version: 2.1
Name: classification-reportzr
Version: 0.0.1b2
Summary: Automate machine learning classification task report for Pak Zuherman
Home-page: https://github.com/khalidm31415/classification-reportzr
License: UNKNOWN
Description: # Classification Reportzr
        Automate machine learning classification task report for Pak Zuherman
        
        ## Install
        ```bash
        pip install classification-reportzr
        ```
        
        ## Usage
        ### Setting-up the experiment
        ```python
        from sklearn import datasets
        from sklearn.svm import SVC
        
        from classification_reportzr.reporterzr import Reporterzr
        
        digits = datasets.load_digits()
        samples, labels = digits.data[:-1], digits.target[:-1]
        
        svc_kwargs = {'C':100.0, 'gamma':0.001}
        svc_reporter = Reporterzr(EstimatorClass=SVC, estimator_kwargs=svc_kwargs, samples=samples, labels=labels, random_state=3)
        
        # `test_sizes` defaults to [0.1, ..., 0.9]
        svc_reporter.run_experiment(test_sizes=[0.1, 0.2])
        ```
        
        ### Get Accuracy Report
        ```python
        print(svc_reporter.get_accuracy_report())
        ```
        prints
        ```
           train_accuracy  test_accuracy  test_size
        0             1.0       0.994444        0.1
        1             1.0       0.988889        0.2
        ```
        
        ### Get Classification Report
        ```python
        print(svc_reporter.get_classification_report(test_size=0.1, split='train'))
        ```
        prints
        ```
                      precision    recall  f1-score   support
        
                   0       1.00      1.00      1.00       160
                   1       1.00      1.00      1.00       164
                   2       1.00      1.00      1.00       159
                   3       1.00      1.00      1.00       164
                   4       1.00      1.00      1.00       163
                   5       1.00      1.00      1.00       164
                   6       1.00      1.00      1.00       163
                   7       1.00      1.00      1.00       161
                   8       1.00      1.00      1.00       156
                   9       1.00      1.00      1.00       162
        
            accuracy                           1.00      1616
           macro avg       1.00      1.00      1.00      1616
        weighted avg       1.00      1.00      1.00      1616
        ```
        
        ### Present All Classification Report
        ```python
        svc_reporter.present_all_classification_report()
        ```
        prints
        ```
        Test size: 0.1
        ==================================================
        Classification report on train data
                      precision    recall  f1-score   support
        
                   0       1.00      1.00      1.00       160
                   1       1.00      1.00      1.00       164
                   2       1.00      1.00      1.00       159
                   3       1.00      1.00      1.00       164
                   4       1.00      1.00      1.00       163
                   5       1.00      1.00      1.00       164
                   6       1.00      1.00      1.00       163
                   7       1.00      1.00      1.00       161
                   8       1.00      1.00      1.00       156
                   9       1.00      1.00      1.00       162
        
            accuracy                           1.00      1616
           macro avg       1.00      1.00      1.00      1616
        weighted avg       1.00      1.00      1.00      1616
        
        ==================================================
        Classification report on test data
                      precision    recall  f1-score   support
        
                   0       1.00      1.00      1.00        18
                   1       1.00      1.00      1.00        18
                   2       1.00      1.00      1.00        18
                   3       1.00      1.00      1.00        19
                   4       1.00      1.00      1.00        18
                   5       1.00      0.94      0.97        18
                   6       1.00      1.00      1.00        18
                   7       1.00      1.00      1.00        18
                   8       1.00      1.00      1.00        17
                   9       0.95      1.00      0.97        18
        
            accuracy                           0.99       180
           macro avg       0.99      0.99      0.99       180
        weighted avg       0.99      0.99      0.99       180
        
        ================================================== 
         ================================================== 
        
        
        
        Test size: 0.2
        ==================================================
        Classification report on train data
                      precision    recall  f1-score   support
        
                   0       1.00      1.00      1.00       142
                   1       1.00      1.00      1.00       145
                   2       1.00      1.00      1.00       142
                   3       1.00      1.00      1.00       146
                   4       1.00      1.00      1.00       145
                   5       1.00      1.00      1.00       146
                   6       1.00      1.00      1.00       145
                   7       1.00      1.00      1.00       143
                   8       1.00      1.00      1.00       138
                   9       1.00      1.00      1.00       144
        
            accuracy                           1.00      1436
           macro avg       1.00      1.00      1.00      1436
        weighted avg       1.00      1.00      1.00      1436
        
        ==================================================
        Classification report on test data
                      precision    recall  f1-score   support
        
                   0       1.00      1.00      1.00        36
                   1       1.00      1.00      1.00        37
                   2       1.00      1.00      1.00        35
                   3       1.00      0.97      0.99        37
                   4       1.00      1.00      1.00        36
                   5       0.97      0.94      0.96        36
                   6       1.00      1.00      1.00        36
                   7       1.00      1.00      1.00        36
                   8       1.00      1.00      1.00        35
                   9       0.92      0.97      0.95        36
        
            accuracy                           0.99       360
           macro avg       0.99      0.99      0.99       360
        weighted avg       0.99      0.99      0.99       360
        
        ================================================== 
         ================================================== 
        ```
Keywords: classification report,laporan klasifikasi,zuherman,zr
Platform: UNKNOWN
Requires-Python: >=3.6
Description-Content-Type: text/markdown
