Artificial Intelligence and Machine Learning MCQs | STS IBA FPSC BPSC SPSC PPSC Mcqs Test Preparation
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Which of the following is a type of ‘deep learning’ model?
A. Convolutional Neural Network (CNN)
B. Decision Tree
C. Naive Bayes
D. K-means Clustering
Answer: Convolutional Neural Network (CNN)
What does ‘hyperparameter optimization’ involve?
A. Finding the best set of hyperparameters for a machine learning model
B. Choosing the best features for the model
C. Normalizing the data
D. Selecting the best model for the dataset
Answer: Finding the best set of hyperparameters for a machine learning model
What is ‘bagging’ in ensemble learning?
A. A method that involves training multiple models on different subsets of data and combining their predictions
B. A technique to reduce the number of features in a dataset
C. A way to optimize a single model's parameters
D. A method to select the best model from a set of models
Answer: A method that involves training multiple models on different subsets of data and combining their predictions
Which algorithm is commonly used for ‘dimensionality reduction’?
A. Principal Component Analysis (PCA)
B. Support Vector Machine (SVM)
C. K-means Clustering
D. Random Forest
Answer: Principal Component Analysis (PCA)
What is ‘early stopping’ in training neural networks?
A. A technique to stop training when the model's performance ceases to improve
B. A method to increase the number of training epochs
C. A way to reduce the learning rate
D. A technique to perform feature scaling
Answer: A technique to stop training when the model's performance ceases to improve
What is ‘gradient descent’ used for?
A. Optimizing the parameters of a machine learning model
B. Scaling the features of a dataset
C. Selecting the best model for a dataset
D. Performing dimensionality reduction
Answer: Optimizing the parameters of a machine learning model
Which of the following techniques is used for dimensionality reduction?
A. Principal Component Analysis (PCA)
B. K-means Clustering
C. Logistic Regression
D. Naive Bayes
Answer: Principal Component Analysis (PCA)
What does the ‘AUC-ROC’ curve measure?
A. The performance of a classification model
B. The performance of a regression model
C. The clustering quality of a dataset
D. The dimensionality reduction effectiveness
Answer: The performance of a classification model
Which algorithm is known for its use of ‘feature importance’?
A. Random Forest
B. K-means Clustering
C. Principal Component Analysis (PCA)
D. Support Vector Machine (SVM)
Answer: Random Forest