streamingtimeseries properties
The Streaming Time Series node builds
and scores time series models in one step.
Example
stream = modeler.script.stream()
typenode = stream.findByID("id42KW3MSA94B")
node = stream.createAt("ts_streaming", "Streaming Time Series", 200, 200)
stream.link(typenode, node)
node.setPropertyValue("custom_fields", True)
node.setPropertyValue("arima", [1,2,3,4,5,6])
node.setPropertyValue("candidate_inputs", ["Na", "K"])
node.setPropertyValue("targets", ["Age"])
node.setKeyedPropertyValue("tf_arima", "Na", [1,2,3,4,5,6,10,"None"])
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 for more information. |
candidate_inputs
|
[field1 ... fieldN] | Input or predictor fields used by the model. |
use_period
|
flag | |
date_time_field
|
field | |
input_interval
|
None
Unknown
Year
Quarter
Month
Week
Day
Hour
Hour_nonperiod
Minute
Minute_nonperiod
Second
Second_nonperiod |
|
period_field
|
field | |
period_start_value
|
integer | |
num_days_per_week
|
integer | |
start_day_of_week
|
Sunday
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday |
|
num_hours_per_day
|
integer | |
start_hour_of_day
|
integer | |
timestamp_increments
|
integer | |
cyclic_increments
|
integer | |
cyclic_periods
|
list | |
output_interval
|
None
Year
Quarter
Month
Week
Day
Hour
Minute
Second |
|
is_same_interval
|
flag | |
cross_hour
|
flag | |
aggregate_and_distribute
|
list | |
aggregate_default
|
Mean
Sum
Mode
Min
Max |
|
distribute_default
|
Mean
Sum |
|
group_default
|
Mean
Sum
Mode
Min
Max |
|
missing_imput
|
Linear_interp
Series_mean
K_mean
K_median
Linear_trend |
|
k_span_points
|
integer | |
use_estimation_period
|
flag | |
estimation_period
|
Observations
Times
|
|
date_estimation
|
list | Only available if you use date_time_field. |
period_estimation
|
list | Only available if you use use_period. |
observations_type
|
Latest
Earliest
|
|
observations_num
|
integer | |
observations_exclude
|
integer | |
method
|
ExpertModeler
Exsmooth
Arima
|
|
expert_modeler_method
|
ExpertModeler
Exsmooth
Arima
|
|
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
|
Simple
HoltsLinearTrend
BrownsLinearTrend
DampedTrend
SimpleSeasonal
WintersAdditive
WintersMultiplicative
DampedTrendAdditive
DampedTrendMultiplicative
MultiplicativeTrendAdditive
MultiplicativeSeasonal
MultiplicativeTrendMultiplicative
MultiplicativeTrend |
|
futureValue_type_method |
Compute
specify |
|
exsmooth_transformation_type
|
None
SquareRoot
NaturalLog
|
|
arima.p
|
integer | |
arima.d
|
integer | |
arima.q
|
integer | |
arima.sp
|
integer | |
arima.sd
|
integer | |
arima.sq
|
integer | |
arima_transformation_type
|
None
SquareRoot
NaturalLog
|
|
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
|
None
SquareRoot
NaturalLog
|
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. |