Accuracy of classifier refers to the ability of classifier.
It predicts the class label correctly and the accuracy of the predictor refers to how well a given predictor can guess the value of predicted attribute for a new data.
Speed :
This refers to the computational cost in generating and using the classifier or predictor.
Robustness:
It refers to the ability of classifier or predictor to make correct prediction from given noisy data.
Scalability:
Scalability refers to the ability to construct the classifier or predictor efficiently; given large amount of data.
Interpretability:
It refers to what extent the classifier or predictor understands.
Accuracy of classifier refers to the ability of classifier. It predicts the class label correctly and the accuracy of the predictor refers to how well a given predictor can guess the value of predicted attribute for a new data.
This refers to the computational cost in generating and using the classifier or predictor.
It refers to the ability of classifier or predictor to make correct prediction from given noisy data.
Scalability refers to the ability to construct the classifier or predictor efficiently; given large amount of data.
It refers to what extent the classifier or predictor understands.