streamingtimeseries properties
streamingtimeseries properties ![Streaming TS node icon](https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/scripting_guide/clementine/images/timeseriesprocessnode.png)The Streaming Time Series node builds and scores time series models in one step. streamingtimeseries properties Table 1. streamingtimeseries properties streamingtimeseries properties Values Property description targets field The Streaming TS node forecasts one or more targets, optionally using one or more input fields as predictors. Frequency and weight fields aren't used. See [Common modeling node properties](https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/scripting_guide/clementine/modelingnodeslots_common.htmlmodelingnodeslots_common) for more information. candidate_inputs [field1 ... fieldN] Input or predictor fields used by the model. use_period flag date_time_field field input_interval NoneUnknownYearQuarterMonthWeekDayHourHour_nonperiodMinuteMinute_nonperiodSecondSecond_nonperiod period_field field period_start_value integer num_days_per_week integer start_day_of_week SundayMondayTuesdayWednesdayThursdayFridaySaturday num_hours_per_day integer start_hour_of_day integer timestamp_increments integer cyclic_increments integer cyclic_periods list output_interval NoneYearQuarterMonthWeekDayHourMinuteSecond is_same_interval flag cross_hour flag aggregate_and_distribute list aggregate_default MeanSumModeMinMax distribute_default MeanSum group_default MeanSumModeMinMax missing_imput Linear_interpSeries_meanK_meanK_medianLinear_trend k_span_points integer use_estimation_period flag estimation_period ObservationsTimes date_estimation list Only available if you use date_time_field. period_estimation list Only available if you use use_period. observations_type LatestEarliest observations_num integer observations_exclude integer method ExpertModelerExsmoothArima expert_modeler_method ExpertModelerExsmoothArima consider_seasonal flag detect_outliers flag expert_outlier_additive flag expert_outlier_innovational flag expert_outlier_level_shift flag expert_outlier_transient flag expert_outlier_seasonal_additive flag expert_outlier_local_trend flag expert_outlier_additive_patch flag consider_newesmodels flag exsmooth_model_type SimpleHoltsLinearTrendBrownsLinearTrendDampedTrendSimpleSeasonalWintersAdditiveWintersMultiplicativeDampedTrendAdditiveDampedTrendMultiplicativeMultiplicativeTrendAdditiveMultiplicativeSeasonalMultiplicativeTrendMultiplicativeMultiplicativeTrend futureValue_type_method Computespecify exsmooth_transformation_type NoneSquareRootNaturalLog arima.p integer arima.d integer arima.q integer arima.sp integer arima.sd integer arima.sq integer arima_transformation_type NoneSquareRootNaturalLog arima_include_constant flag tf_arima.p.fieldname integer For transfer functions. tf_arima.d.fieldname integer For transfer functions. tf_arima.q.fieldname integer For transfer functions. tf_arima.sp.fieldname integer For transfer functions. tf_arima.sd.fieldname integer For transfer functions. tf_arima.sq.fieldname integer For transfer functions. tf_arima.delay.fieldname integer For transfer functions. tf_arima.transformation_type.fieldname NoneSquareRootNaturalLog For transfer functions. arima_detect_outliers flag arima_outlier_additive flag arima_outlier_level_shift flag arima_outlier_innovational flag arima_outlier_transient flag arima_outlier_seasonal_additive flag arima_outlier_local_trend flag arima_outlier_additive_patch flag conf_limit_pct real events fields forecastperiods integer extend_records_into_future flag conf_limits flag noise_res flag max_models_output integer Specify the maximum number of models you want to include in the output. Note that if the number of models built exceeds this threshold, the models aren't shown in the output but they're still available for scoring. Default value is 10. Displaying a large number of models may result in poor performance or instability. custom_fields boolean This option tells the node to use the field information specified here instead of that given in any upstream Type node(s). After selecting this option, specify the following fields as required. arima array A list with p, d, q, sp, sd, sq. tf_arima array A list with name, p, q, d, sp, sq, sd, delay and type.