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 only
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