Metadata-Version: 2.1
Name: classification-reportzr
Version: 0.0.1b8
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 -U classification-reportzr
        ```
        
        ## Test
        
        ```bash
        pytest -v
        ```
        
        ## Usage
        
        ### Setting-up the experiment
        
        ```python
        from sklearn import datasets
        from sklearn.svm import SVC
        
        from reporterzr import Reporterzr
        
        iris = datasets.load_iris()
        samples, labels = iris.data[:-1], iris.target[:-1]
        
        param_grid = {
            'C': [10,50,100],
            'gamma': [0.005,0.05,0.5],
            'kernel': ['poly', 'rbf', 'linear']
        }
        svc_reporter = Reporterzr(SVC, param_grid)
        ```
        
        ### Run The Experiment
        
        ```python
        # `test_sizes` defaults to [0.1, ..., 0.9]
        # `repetition` defaults to 10
        report = svc_reporter.run_experiment(samples, labels, test_sizes=[0.1, 0.2], repetition=5)
        print(report)
        ```
        
        prints
        
        ```
           Test Size   C  gamma  kernel                     Train Accuracies  \
        0        0.1  10  0.005    poly  [0.881, 0.896, 0.888, 0.881, 0.873]
        1        0.1  10  0.005     rbf     [0.978, 0.978, 0.97, 0.97, 0.97]
        2        0.1  10  0.005  linear  [0.978, 0.978, 0.978, 0.978, 0.978]
        3        0.1  10  0.050    poly  [0.978, 0.978, 0.978, 0.978, 0.978]
        4        0.1  10  0.050     rbf  [0.993, 0.985, 0.993, 0.985, 0.985]
        
           Max Train  Mean Train  Stdev Train                    Test Accuracies  \
        0      0.896       0.884        0.008        [0.933, 0.8, 0.8, 1.0, 1.0]
        1      0.978       0.973        0.004  [0.933, 0.867, 0.933, 0.8, 0.933]
        2      0.978       0.978        0.000      [0.933, 1.0, 1.0, 0.933, 1.0]
        3      0.978       0.978        0.000          [1.0, 1.0, 1.0, 1.0, 1.0]
        4      0.993       0.988        0.004      [0.933, 1.0, 0.933, 1.0, 1.0]
        
           Max Test  Mean Test  Stdev Test  \
        0     1.000      0.907       0.090
        1     0.933      0.893       0.053
        2     1.000      0.973       0.033
        3     1.000      1.000       0.000
        4     1.000      0.973       0.033
        
                                        Experiment Times
        0   [0.00086, 0.00076, 0.0007, 0.00071, 0.00069]
        1  [0.00075, 0.00075, 0.00073, 0.00074, 0.00074]
        2  [0.00048, 0.00046, 0.00046, 0.00045, 0.00046]
        3  [0.00046, 0.00049, 0.00048, 0.00048, 0.00047]
        4  [0.00061, 0.00058, 0.00057, 0.00059, 0.00059]
        ```
        
Keywords: classification report,laporan klasifikasi,zuherman,zr
Platform: UNKNOWN
Requires-Python: >=3.6
Description-Content-Type: text/markdown
