NSCT – Pattern Recognition & Generalization MCQs 20 min Score: 0 Attempted: 0/20 Subscribe 1. . Pattern recognition is: (A) The process of identifying regularities, structures, or trends in data (B) Encrypting data only (C) Compressing files only (D) Backup onlyShow All Answers 2. . Generalization in pattern recognition means: (A) Applying learned patterns from specific examples to new, unseen instances (B) Encrypting files (C) Compressing data (D) Backup only 3. . Types of patterns in data include: (A) Only compressed files (B) Only encrypted data (C) Sequences, spatial patterns, temporal patterns, and structural patterns (D) Backup only 4. . Feature extraction in pattern recognition is: (A) Backup only (B) Encrypting data (C) Compressing data (D) Selecting and transforming relevant attributes from raw data for analysis 5. . Supervised learning in pattern recognition involves: (A) Backup only (B) Encrypting files (C) Compressing files (D) Learning patterns from labeled data 6. . Unsupervised learning in pattern recognition involves: (A) Backup only (B) Encrypting files (C) Compressing files (D) Finding patterns or clusters in unlabeled data 7. . Classification is: (A) Encrypting data (B) Assigning input data to predefined categories based on learned patterns (C) Compressing data (D) Backup only 8. . Clustering is: (A) Compressing files (B) Encrypting files (C) Grouping similar data points together without predefined labels (D) Backup only 9. . Pattern recognition is used in: (A) Image recognition, speech recognition, handwriting recognition, and biometrics (B) Encrypting files only (C) Compressing files only (D) Backup only 10. . Noise in pattern recognition refers to: (A) Irrelevant or random variations in data that can affect accuracy (B) Encryption errors (C) Compression errors (D) Backup errors 11. . Template matching in pattern recognition involves: (A) Comparing input data with stored templates to find the best match (B) Encrypting data (C) Compressing files (D) Backup only 12. . Feature selection helps to: (A) Backup only (B) Encrypt data (C) Compress files (D) Reduce dimensionality and improve recognition accuracy 13. . Decision boundaries in pattern recognition are: (A) Backup only (B) Encryption boundaries (C) Compression boundaries (D) Lines or surfaces that separate different classes in feature space 14. . Overfitting occurs when: (A) Backup only (B) Encrypting files too much (C) Compressing data excessively (D) A model fits training data too closely and fails to generalize to new data 15. . Underfitting occurs when: (A) Backup only (B) Encrypting files (C) Compressing files (D) A model is too simple to capture patterns in the data 16. . Applications of generalization include: (A) Compressing files (B) Encrypting files (C) Predictive analytics, AI models, and machine learning systems (D) Backup only 17. . Neural networks are used in pattern recognition for: (A) Encrypting data (B) Learning complex non-linear patterns in data (C) Compressing files (D) Backup only 18. . Statistical pattern recognition involves: (A) Using probability and statistical techniques to classify data (B) Encrypting data (C) Compressing data (D) Backup only 19. . Advantages of pattern recognition and generalization include: (A) Backup only (B) Only encryption (C) Only compression (D) Automation, predictive capability, and handling large volumes of data 20. . The main purpose of pattern recognition and generalization is to: (A) Identify meaningful patterns in data and apply learned knowledge to new situations (B) Encrypt data (C) Compress files (D) Backup tables
