Machine Learning Classification Quiz Posted by iammtabdullah Date July 22, 2025 Comments 0 comment Welcome to your Machine Learning Classification Quiz 01. What is the formula for F1-score? (Precision + Recall) / 2 2× (Precision × Recall) / (Precision + Recall) (Accuracy + Recall) / 2 None 02. Which of the following is NOT an evaluation metric for classification models? Precision Recall Mean Squared Error (MSE) None 03. What does the K in K-Nearest Neighbors (KNN) represent? The number of nearest neighbors The number of clusters The number of input features None 04. Which of the following represents a perfect classifier in an ROC curve? AUC=0.5 AUC=1 AUC=0 None 05. What does a confusion matrix NOT include? True Positives False Negatives Accuracy None 06. A model has Precision = 0.8 and Recall = 0.5. What is the F1-score? 0.6 0.65 0.8 None 07. What is the formula for Precision? TP / (TP + FN) TP / (TP + FP) (Precision + Recall) / 2 None 08. What is the formula for Recall? TP / (TP + FN) TP / (TP + FP) (Precision + Recall) / 2 None 09. Why is accuracy NOT a good metric? When the dataset is balanced When the dataset is highly imbalanced When there are no missing values None 10. If a classifier has AUC = 0.5, what does it mean? The model is making random predictions The model is perfect The model is completely wrong None 11. What is Classification in Machine Learning? A technique used to group data into predefined categories A method to predict continuous numerical values A way to store data in a database None 12. Which of the following is a classification algorithm? K-Means Logistic Regression Linear Regression None Time's up iammtabdullah Previous post Assignment – 08 (CKD Prediction Using ML Classification Algorithms) July 22, 2025 Next post Assignment 05 - Intermediate CSS Flag July 27, 2025
