linearasnode properties | IBM Cloud Pak for Data as a Service

linearasnode properties

Linear-AS node icon Linear regression models predict a continuous target based on linear relationships between the target and one or more predictors.

Table 1. linearasnode properties
`linearasnode` Properties	Values	Property description
`target`	field	Specifies a single target field.
`inputs`	[field1 ... fieldN]	Predictor fields used by the model.
`weight_field`	field	Analysis field used by the model.
`custom_fields`	flag	The default value is `TRUE`.
`intercept`	flag	The default value is `TRUE`.
`detect_2way_interaction`	flag	Whether or not to consider two way interaction. The default value is `TRUE`.
`cin`	number	The interval of confidence used to compute estimates of the model coefficients. Specify a value greater than 0 and less than 100. The default value is `95`.
`factor_order`	`ascending` `descending`	The sort order for categorical predictors. The default value is `ascending`.
`var_select_method`	`ForwardStepwise` `BestSubsets` `none`	The model selection method to use. The default value is `ForwardStepwise`.
`criteria_for_forward_stepwise`	`AICC` `Fstatistics` `AdjustedRSquare` `ASE`	The statistic used to determine whether an effect should be added to or removed from the model. The default value is `AdjustedRSquare`.
`pin`	number	The effect that has the smallest p-value less than this specified `pin` threshold is added to the model. The default value is `0.05`.
`pout`	number	Any effects in the model with a p-value greater than this specified `pout` threshold are removed. The default value is `0.10`.
`use_custom_max_effects`	flag	Whether to use max number of effects in the final model. The default value is `FALSE`.
`max_effects`	number	Maximum number of effects to use in the final model. The default value is `1`.
`use_custom_max_steps`	flag	Whether to use the maximum number of steps. The default value is `FALSE`.
`max_steps`	number	The maximum number of steps before the stepwise algorithm stops. The default value is `1`.
`criteria_for_best_subsets`	`AICC` `AdjustedRSquare` `ASE`	The mode of criteria to use. The default value is `AdjustedRSquare`.