Forms predictions from a radial basis function model fitted by
|Controls fitted output (
||X-values at which to predict|
||Details of the fitted model|
RBPREDICT forms predictions using radial basis function model fitted by
RBFIT. Details of the the model and the estimated parameters are supplied using the
SAVE parameter. This must have been saved using the
SAVE parameter of
RBFIT. If this is not set, the output is from the most recent model fitted by
RBFIT. The values of the x-variates at which to predict are supplied, in a pointer, using the
X parameter. The variates in the pointer must be in exactly the same order as the equivalent variates in the pointer defined for the
X parameter in the original
The output is controlled by the
||a description of the model,|
RBPREDICT uses the function
nagdmc_predict_RBF from the Numerical Algorithms Group’s library of Data Mining Components (DMCs).
You can restrict the set of units used for the prediction by applying a restriction to any of the x-variates. If several of these are restricted, they must all be restricted to the same set of units.
Commands for: Data mining.
CAPTION 'RBPREDICT example',\ 'Predicting the grape cultivar from 13 wine attributes'; STYLE=meta,plain SPLOAD '%Data%/WinesTrain.gsh'; ISAVE=pData POINTER [VALUES=pData[2...14]] Attributes GROUPS Wine; FACTOR=Cultivar TABULATE [CLASS=Cultivar] Attributes; MEANS=Mn[1...13] RBFIT [PRINT=*; RBTYPE=linear; LAMBDA=10] Y=Wine; X=Attributes; \ CENTRES=Mn; SAVE=RBSave "Predictions for wines from unknown cultivars from fitted model" SPLOAD '%Data%/WinesPred.gsh'; ISAVE=TestAttr RBPREDICT X=TestAttr; PREDICTIONS=Fit; SAVE=RBSave "Predicted class is closest integer 1...3" VARIATE Prediction; VALUES = 1 + (Fit > 1.5) + (Fit > 2.5) GROUPS Prediction; Pred_Cultivar TABULATE [CLASS=Pred_Cultivar; PRINT=counts]