Problem 1:
1. Load the wine dataset from sklearn (use load_wine).
2. Scale attributes using StandardScaler
3. Use 70% data for training.
4. Make prediction on the 30% data using KNN.
5. Print the F1 score (only) for each class
Solution
Problem 1:
1. Load the wine dataset from sklearn (use load_wine).
2. Scale attributes using StandardScaler
3. Use 70% data for training.
4. Make prediction on the 30% data using KNN.
5. Print the F1 score (only) for each class
Solution