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• Once the all the training data are acquired, the training module performs preprocessing to convert the data from JSON format into Dictionary format
• In Preprocessing the training Data is normalized and Transformed.
• The preprocessed data (PM data Parameters data content) for all slices and cells which are in time series are converted into forecast series.
  • The forecast series is cells PM data parameters for current time instance, Plus the previous past or last four time instance data.
  • Similar forecast series data is prepared for all the cells in the slice.
• Data are split into training and validation datasets
• The expected results for each time instance cell data are synthetically generated based on rule conditions and the cell intends.
  •  Sample training data referred at following source code location components/ml-prediction-ms/train/ExampleSample_train_data_s1.xlsx
  • P.S: This fill is only for reference, on how the training data are prepared. In actual training process, the data are fetched  RANSim topic.
  • Following wiki attached excel file contains sample cell data from a slice. Here each of the cell's timeseries data will appended from first cells to the last cell its time series successive to that  slice. This append timeseries data from all the cells from a slice will create a large training data block..

  • Spreadsheets
    containerType page documentId ExampleSample_train_data_s1_smaller.xlsx_0.ssc isNew false containerId 137199794137199826 title ExampleSample_train_data_s1_smaller.xlsx

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• The training module perform Training against an LSTM model.
• The Training model file are archived.
• The results are manually verified .

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