Prediction problems: Classification vs. Numeric Prediction Classification predicts categorical class labels(discrete or nominal) classifies data(constructs a model) based on the training set and the values (class labels)in a classifying attribute and uses it in classifying new data ■ Numeric Prediction models continuous-valued functions, i.e. predicts unknown or missing values Typical applications Credit/loan approval Medical diagnosis: if a tumor is cancerous or benign a fraud detection: if a transaction is fraudulent u Web page categorization: which category it is 55 ◼ Classification ◼ predicts categorical class labels (discrete or nominal) ◼ classifies data (constructs a model) based on the training set and the values (class labels) in a classifying attribute and uses it in classifying new data ◼ Numeric Prediction ◼ models continuous-valued functions, i.e., predicts unknown or missing values ◼ Typical applications ◼ Credit/loan approval: ◼ Medical diagnosis: if a tumor is cancerous or benign ◼ Fraud detection: if a transaction is fraudulent ◼ Web page categorization: which category it is Prediction Problems: Classification vs. Numeric Prediction