Metadata-Version: 2.1
Name: autoth
Version: 0.0.1
Summary: Automatic threshold optimization
Home-page: https://github.com/pypa/sampleproject
Author: Qiuqiang Kong
Author-email: qiuqiangkong@gmail.com
License: UNKNOWN
Description: # Autoth: Automatic optimzie hyper parameters
        
        Autoth is a Python toolbox to automatically optimize hyper parameters to maximize scores. For example, Autoth can optimize hyper parameters to maximize F1 score in a classification task. In practice, Autoth numerically calculate gradients of scores over hyper parameters. Then, the hyper parameters are updated according to the gradients iteratively. Please see [1] for details.
        
        ## Install
        ```
        pip install autoth
        ```
        
        ## Example
        ```
        python3 example.py
        ```
        
        ## Results
        <pre>
        ------ Manually selected hyper parameters ------
        Hyper parameters: [0.3, 0.3, 0.3]
        Score: 0.5556
        
        ------ Automatic optimized hyper parameters ------
        Optimizing hyper parameters ...
        learning rate: 0.010, total epochs: 10
            Hyper parameters: [0.3, 0.31, 0.29], score: 0.5556
            Epoch: 0, Time: 0.0181 s
            Hyper parameters: [0.3, 0.3197, 0.2801], score: 0.5556
            Epoch: 1, Time: 0.0178 s
            Hyper parameters: [0.3, 0.3237, 0.2702], score: 0.5714
            Epoch: 2, Time: 0.0212 s
            Hyper parameters: [0.3, 0.3245, 0.263], score: 0.6099
            Epoch: 3, Time: 0.0144 s
            Hyper parameters: [0.3, 0.3232, 0.2548], score: 0.6099
            Epoch: 4, Time: 0.0142 s
            Hyper parameters: [0.3, 0.3204, 0.2464], score: 0.6099
            Epoch: 5, Time: 0.0151 s
            Hyper parameters: [0.3, 0.3164, 0.2382], score: 0.6099
            Epoch: 6, Time: 0.0159 s
            Hyper parameters: [0.3, 0.316, 0.2302], score: 0.5940
            Epoch: 7, Time: 0.0143 s
            Hyper parameters: [0.3, 0.318, 0.2226], score: 0.5940
            Epoch: 8, Time: 0.0150 s
            Hyper parameters: [0.3, 0.3186, 0.2152], score: 0.6099
            Epoch: 9, Time: 0.0177 s
        
        Optimized hyper parameters: [0.3, 0.3186, 0.2152]
        Score: 0.6099
        </pre>
        
        ## Cite
        [1] Kong, Qiuqiang, Yong Xu, Wenwu Wang, and Mark D. Plumbley. "Sound Event Detection of Weakly Labelled Data with CNN-Transformer and Automatic Threshold Optimization." arXiv preprint arXiv:1912.04761 (2019).
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
