This package provides simple data mining models for SAP Business One.
This package uses JDK 1.8.0 and Weka 3.8.2.
- Download weka.jar and horus.datamining.jar from ./lib to your Java project and add them into build paths.
- Download all .model and .arff files from ./models to a directory as you like. Remember this directory that may be used in your Java code.
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Environment: A data structure that contains configurations used to load models and data.
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Model: An abstract data structure that is used to give suggestions according to the given feature vector.
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Feature Vector: A serial of fields that compose a record for model to solve. Typically, the last field is the field for suggestion, others are for model to use to give the suggestion. Two kinds of fields are supported: numeric and nominal (enumeration). The schema could be found in .arff files.
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Suggestion: The output of a model solution. It may consists of several fields. Usually it consists of one field of the last one of corresponding feature vector.
There is one corresponding wrapper class for each model in package horus.datamining.wrapper. These wrappers provide use of the models without creating model objects or building feature vectors. Only model path specifications and method calls with corresponding parameters are needed. The results are always double arrays. The input and output schemas are specified in the comments of the source code: ./src/horus/datamining/wrapper/*.
You can refer to ./src/horus/datamining/Sample.java as coding example.
- The StockQuantity in feature vector of SaleQuantityPrediction is the stock quantity of yesterday plus the purchase quantity of today.
- The StockQuantity in feature vector of ProfitPrediction is the stock quantity of yesterday.
- In ProfitPrediction, today is the day that is going to sell mantous. Target day is the day whose profit is to be predicted. The sale/purchase price/quantity belong to today, not target day.