Open danyaljj opened 8 years ago
Currently this is how we do pipeline:
object ClassifierLayer1 extends Learnable (node) { def label = labelProperty1 def feature = using(property2, property3,...) } object ClassifierLayer2 extends Learnable (node) { def label = labelProperty2 def feature = using(classifier1Labels, ,...) // using the prediction of the classifier in the previous layer } // defined in data-model val classifier1Labels = new Property(node){ x: Type => ClassifierLayer1(x) }
But we should be able to skip the definition of the extra property classifier1Labels and just do:
classifier1Labels
object ClassifierLayer1 extends Learnable (node) { def label = labelProperty1 def feature = using(property2, property3,...) } object ClassifierLayer2 extends Learnable (node) { def label = labelProperty2 def feature = using(ClassifierLayer1, ,...) }
This is slightly trickier when the type of the node parameters for the two classifiers are not the same.
Currently this is how we do pipeline:
But we should be able to skip the definition of the extra property
classifier1Labels
and just do:This is slightly trickier when the type of the node parameters for the two classifiers are not the same.