Metadata-Version: 1.1
Name: Kami
Version: 0.3.8
Summary: Forecast sales with Entity Embedding LSTM
Home-page: https://github.com/MacarielAerial
Author: Yifei Yu
Author-email: yyu.mam2020@london.edu
License: MIT
Download-URL: https://github.com/MacarielAerial/AM18_SPR20_LondonLAB/archive/V_0.3.8.tar.gz
Description: # AM18_SPR20_LondonLAB
        
        The package contains two functions: Preprocess and Analyse.
        
        Preprocess has two arguments: 1. Path to the grouped product sales input data
        			      2. Path to an intermediary folder to store intermediary data
        
        Analyse has two arguments as well: 1. Path to an output folder to store final output
        				   2. Path to the intermediary folder specified during Preprocess
        
        Vis has two arguments: 1. Path to an output folder to store plots
        		       2. Path to the intermediary folder specified during Preprocess
        
        Forecast has 6 arguments: 1. Path to an output folder to store final predictions
        		        2. Path to the intermediary folder specified during Preprocess
        		        3. A list of stores whose sales are predicted
        		        4. A list of products whose sales are predicted
        		        5. The start date of predictions
        		        6. The end date of predictions
        
        To obtain final results, call Preprocess and Analyse sequentially with their respective arguments after setting up the intermediary and the output folder
        
Keywords: SALES,FORECAST,LSTM,EMBEDDING
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
