Metadata-Version: 1.1
Name: timeseriesprocessing
Version: 0.0.1
Summary: Time Series Processing Using Regression
Home-page: https://github.com/george-j-zhu/timeseriesprocessing
Author: Jiajun Zhu
Author-email: george.choo@outlook.com
License: UNKNOWN
Description-Content-Type: UNKNOWN
Description: # Precessing timeseries problems using Regression
        This is a simple framework to process multi-variable timeseries dataset using regression.<br>
        
        Most time series analysis methods focus on single variable data. It's simple to understand<br>
        and work with such data. But sometimes our time series dataset may containe multi-varibles.<br>
        For example, in marketing analysis, profit of a day may not only be decided by the number<br>
        of customers, but also depend on campaign, CM and so on.<br>
        It is harder to model such problems and often many of the classical methods do not perform<br>
        well.<br>
        
        Since regression methods are good at processing multivarible, we can simply turn our timeseries<br>
        dataset into training dataset for regression by exluding time columns.<br>
        
        ## Restrictions
        In general when using regression methods, timeseries data for your independent variables must be<br>
        avaliable to make predicitons.<br>
        
        ## How to use
        See example.ipynb
        
Keywords: Time Series Processing Using Regression
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
