dlpy.timeseries.TimeseriesTable.prepare_subsequences

TimeseriesTable.prepare_subsequences(seq_len, target, predictor_timeseries=None, timeid=None, groupby=None, input_length_name='xlen', target_length_name='ylen', missing_handling='drop')

Prepare the subsequences that will be pass into RNN

Parameters

seq_lenint

subsequence length that will be passed onto RNN.

targetstring

the target variable for RNN. Currenly only support univariate target, so only string is accepted here, not list of strings.

predictor_timeseriesstring or list-of-strings, optional

Timeseries that will be used to predict target. They will be preprocessed into subsequences as well. If None, it will take the target timeseries as the predictor, which corresponds to auto-regressive models. Default: None

timeidstring, optional

Specifies the column name for the timeid. If None, it will take the timeid specified in timeseries_accumlation. Default: None

groupbystring or list-of-strings, optional

The groupby variables. if None, it will take the groupby specified in timeseries_accumlation. Default: None

input_length_namestring, optional

The column name in the CASTable specifying input sequence length. Default: xlen

target_length_namestring, optional

The column name in the CASTable specifying target sequence length. currently target length only support length 1 for numeric sequence. Default: ylen

missing_handlingstring, optional

How to handle missing value in the subsequences. default: drop