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In the context of anomaly detection, which is the primary advantage of using autoencoders?
Response:
A. They can handle both structured and unstructured data
B. They reduce the dimensionality of the input data
C. They are capable of detecting complex, non-linear anomalies
D. They are faster to train than traditional algorithms
Answer: C
NEW QUESTION # 139
What is the primary challenge addressed by 'class imbalance' techniques in machine learning?
Response:
A. Reducing the dimensionality of the dataset
B. Optimizing the model for better accuracy
C. Improving the computational efficiency of the model
D. Handling datasets where some classes are much more frequent than others
Answer: D
NEW QUESTION # 140
You are using a CNN to classify images in a dataset. After several epochs of training, you notice that the model performs well on the training set but poorly on the validation set. This suggests overfitting.
What steps should you take to improve the generalization of the model?
Response:
A. Implement dropout in the fully connected layers, apply data augmentation to increase the variability of the training data, and consider early stopping to prevent overfitting
B. Remove padding to simplify the architecture
C. Reduce the size of the dataset and increase the number of convolutional layers
D. Train the model for more epochs and reduce the use of regularization
Answer: A
NEW QUESTION # 141
What is the scikit-learn library in Python best used for?
Response:
A. High-performance computing
B. Machine learning model development
C. Advanced data visualization
D. Large-scale data processing
Answer: B
NEW QUESTION # 142
What is the role of the centroid in the k-means clustering algorithm?
Response:
A. It represents the boundary between two clusters
B. It serves as the initial seed for the clustering process
C. It is the geometric center of a cluster, representing the mean of the data points in that cluster
D. It is the point that minimizes the error in each cluster
Answer: C
NEW QUESTION # 143
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