Predict time series based on a given ClassificationTS model.

# S3 method for ClassificationTS
predict(model, data, key = NULL, thread.ratio = NULL)

Arguments

data

DataFrame
Input data. The data must be structured the same as the data used in the hanaml.ClassificationTS().

key

character, optional
Specifies the column name in data that represents the order of time-series.

thread.ratio

double, optional
Controls the proportion of available threads that can be used by this function.
The value range is from 0 to 1, where 0 indicates a single thread, and 1 indicates all available threads.
Values between 0 and 1 will use up to that percentage of available threads.Values outside this range are ignored.
Defaults to 0.

Value

DataFrame

  • The predict result based on a given ClassificationTS model.

Examples


> tsc <- hanaml.ClassificationTS(data=df, label=label, key = 'ID')
> res <- transform(tsc, data=df.predict, key= 'ID')
> res$Collect()