Predict method for LSTM

# S3 method for LSTM
predict(model, data, top.k.attributions = NULL, ...)

Arguments

data

DataFrame
Data for prediction. Every row in the data should contain one piece of record data for prediction, i.e. it should be structured as follows:

  • First column: Record ID, type INTEGER.

  • Other columns: Time-series and external data values, arranged in time order.

The number of all columns but the first ID column should be equal to time.dim * (M + 1), where M is the number of exogenous variables of the input data in the training phase.

top.k.attributions

integer, optional
Specifies the number of features with highest attributions to output.
Defaults to 10.

Value

DataFrame
Forecasted values, structured as follows:

  • ID: type INTEGER, timestamp.

  • VALUE: type DOUBLE, forecast value.

  • REASON_CODE: type NCLOB, Sorted SHAP values for test data at each time step.

Details

Time-series prediction using LSTM model

See also