Metadata-Version: 2.1
Name: classification-reportzr
Version: 0.0.1b9
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, 0.888, 0.873, 0.888, 0.881]
        1        0.1  10  0.005     rbf   [0.978, 0.955, 0.955, 0.955, 0.97]
        2        0.1  10  0.005  linear    [0.978, 0.97, 0.985, 0.978, 0.97]
        3        0.1  10  0.050    poly  [0.985, 0.978, 0.978, 0.978, 0.985]
        4        0.1  10  0.050     rbf  [0.985, 0.993, 0.993, 0.993, 0.993]
        
           Max Train Acc  Mean Train Acc  Stdev Train Acc  \
        0          0.888           0.882            0.006
        1          0.978           0.963            0.010
        2          0.985           0.976            0.006
        3          0.985           0.981            0.003
        4          0.993           0.991            0.003
        
                               Test Accuracies  Max Test Acc  Mean Test Acc  \
        0      [0.867, 0.867, 1.0, 0.8, 0.933]         1.000          0.893
        1  [0.933, 0.933, 0.933, 0.867, 0.933]         0.933          0.920
        2            [1.0, 1.0, 1.0, 1.0, 1.0]         1.000          1.000
        3          [1.0, 1.0, 1.0, 1.0, 0.933]         1.000          0.987
        4        [0.933, 1.0, 1.0, 0.867, 1.0]         1.000          0.960
        
           Stdev Test Acc                         Experiment Times (sec)
        0           0.068  [0.00095, 0.00077, 0.00072, 0.00077, 0.00074]
        1           0.026   [0.00079, 0.0008, 0.00082, 0.00082, 0.00081]
        2           0.000   [0.0005, 0.00052, 0.00045, 0.00049, 0.00049]
        3           0.027  [0.00052, 0.00055, 0.00052, 0.00054, 0.00053]
        4           0.053  [0.00062, 0.00062, 0.00064, 0.00061, 0.00065]
        ```
        
Keywords: classification report,laporan klasifikasi,zuherman,zr
Platform: UNKNOWN
Requires-Python: >=3.6
Description-Content-Type: text/markdown
