Match the appropriate performance measure with the data mining tasks. F. v Random forest to predict good vs bad credit decisions A. Akaike's Information Criterion B. Customer segments based on k-means B. within-ss elbow, silhoutte F. v Gradient boosted tree based model to predict fraudulent transactions C. total confusion scale (fraud vs non-fraud). D. Cosine similarity A. Selecting from alternate different linear models based on different variables E. MSE, MAE - v Recommender system to predict movie ratings (on 1-5 scale) F. confusion matrix, accuracy, lift G. average distance between cases