Artificial Intelligence and Machine Learning MCQs | STS IBA FPSC BPSC SPSC PPSC Mcqs Test Preparation

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Which of the following is used to prevent the model from memorizing the training data?

A. Regularization
B. Normalization
C. Data Augmentation
D. Feature Engineering

Answer: Regularization

Which of the following is an unsupervised learning algorithm?

A. Support Vector Machine (SVM)
B. Linear Regression
C. K-means Clustering
D. Decision Trees

Answer: K-means Clustering

What is ‘feature scaling’ used for in machine learning?

A. To reduce the number of features
B. To normalize feature values to a common scale
C. To increase the complexity of the model
D. To create new features

Answer: To normalize feature values to a common scale

What does the term ‘overfitting’ mean in machine learning?

A. The model performs well on training data but poorly on test data
B. The model performs well on test data but poorly on training data
C. The model performs equally well on both training and test data
D. The model has too few parameters

Answer: The model performs well on training data but poorly on test data

Which of the following is a common activation function in neural networks?

A. Linear Function
B. Sigmoid Function
C. Polynomial Function
D. Logarithmic Function

Answer: Sigmoid Function

Which metric is commonly used to evaluate classification models?

A. Mean Squared Error (MSE)
B. Confusion Matrix
C. R-squared
D. Log Loss

Answer: Confusion Matrix

What is the purpose of a loss function in machine learning?

A. To optimize model performance
B. To evaluate model complexity
C. To measure the error of predictions
D. To normalize the data

Answer: To measure the error of predictions

What does the term ‘epoch’ refer to in training neural networks?

A. A single pass through the entire dataset
B. The number of hidden layers
C. The size of the training batch
D. The learning rate

Answer: A single pass through the entire dataset

Which algorithm is used for dimensionality reduction?

A. Decision Trees
B. K-means Clustering
C. Principal Component Analysis (PCA)
D. Naive Bayes

Answer: Principal Component Analysis (PCA)