Metadata-Version: 2.1
Name: scalg
Version: 0.1
Summary: Analyse data file using a range based procentual proximity algorithm and calculate the linear maximum likelihood estimation.
Home-page: https://github.com/markmelnic/Scoring-Algorithm
Author: Mark Melnic
Author-email: commerce.markmelnic@gmail.com
License: MIT
Description: # Scoring-Algorithm
        
        This is an algorithm which works based on a range based procentual proximity principle. Initially it was developed for a personal project, however later I found out it is a form of Newton's method used in statistics to solve maximum likelihood equations numerically.
        
        scalg.score:
        
            Args:
                source_data (list): Data set to process.
                weights (list): Weights corresponding to each column from the data set.
                    0 if lower values have higher weight in the data set,
                    1 if higher values have higher weight in the data set
        
            Optional args:
                "score_lists" (str): Returns a list with lists of each column scores.
                "scores" (str): Returns only the final scores.
        
            Raises:
                ValueError: Weights can only be either 0 or 1 (int)
        
            Returns:
                list: Source data with the score of the set appended at as the last element.
        
        scalg.score_columns:
        
            Args:
                source_data (list): Data set to process.
                weights (list): Weights corresponding to each column from the data set.
                    0 if lower values have higher weight in the data set,
                    1 if higher values have higher weight in the data set
                columns (list): Indexes of the source_data columns to be scored.
        
            Optional args:
                "score_lists" (str): Returns a list with lists of each column scores.
                "scores" (str): Returns only the final scores.
        
            Raises:
                ValueError: Weights can only be either 0 or 1 (int)
        
            Returns:
                list: Source data with the score of the set appended at as the last element.
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
