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Which activation function is commonly used in neural networks?
A. ReLU (Rectified Linear Unit)
B. Principal Component Analysis (PCA)
C. K-means Clustering
D. Naive Bayes
Answer: ReLU (Rectified Linear Unit)
What is ‘Naive Bayes’ used for?
A. Classification tasks
B. Dimensionality reduction
C. Clustering data points
D. Feature scaling
Answer: Classification tasks
Which of the following is an example of a ‘distance metric’ used in clustering algorithms?
A. Euclidean Distance
B. Principal Component Analysis
C. Support Vector Machine
D. Naive Bayes
Answer: Euclidean Distance
What is ‘cross-entropy loss’ used for in machine learning?
A. Evaluating the performance of classification models
B. Optimizing regression models
C. Reducing the dimensionality of the data
D. Scaling features to a common range
Answer: Evaluating the performance of classification models
What is the purpose of ‘feature scaling’?
A. To transform features to a common scale to improve model performance
B. To select the most relevant features for the model
C. To reduce the dimensionality of the data
D. To handle missing values in the dataset
Answer: To transform features to a common scale to improve model performance
Which of the following algorithms is commonly used for ‘classification’ tasks?
A. Decision Trees
B. K-means Clustering
C. Principal Component Analysis
D. Linear Regression
Answer: Decision Trees
Which of the following algorithms is used for ‘regression’ tasks?
A. Linear Regression
B. K-means Clustering
C. Naive Bayes
D. Association Rules
Answer: Linear Regression
What does ‘feature engineering’ involve?
A. Creating new features or modifying existing ones to improve model performance
B. Reducing the number of features in the dataset
C. Scaling features to a common range
D. Selecting the most relevant features from the dataset
Answer: Creating new features or modifying existing ones to improve model performance
What is a ‘confusion matrix’ used for?
A. To evaluate the performance of classification models
B. To visualize the distribution of data points
C. To perform feature selection
D. To reduce the dimensionality of the data
Answer: To evaluate the performance of classification models