Machine Learning MCQs#1. Which of the following is not a type of machine learning algorithm? Unsupervised learning Unsupervised learning Reinforcement learning Reinforcement learning Supervised learning Supervised learning Semi-supervised learning Semi-supervised learning Self-learning Self-learning #2. What is the purpose of a validation set in machine learning? To evaluate the model on data it has never seen before To evaluate the model on data it has never seen before To test the model on the training data To test the model on the training data To fine-tune hyperparameters To fine-tune hyperparameters To select features for the model To select features for the model To train the model To train the model #3. Which algorithm is commonly used for classification problems in machine learning? K-means clustering K-means clustering Decision trees Decision trees Principal Component Analysis (PCA) Principal Component Analysis (PCA) Linear regression Linear regression Apriori algorithm Apriori algorithm #4. What is overfitting in machine learning? When the model performs well on the training data but poorly on new, unseen data When the model performs well on the training data but poorly on new, unseen data When the model performs poorly on the training data but well on new, unseen data When the model performs poorly on the training data but well on new, unseen data When the model performs equally well on both training and test data When the model performs equally well on both training and test data When the model is too simple to capture the underlying patterns in the data When the model is too simple to capture the underlying patterns in the data When the model has too few parameters When the model has too few parameters #5. Which activation function is commonly used in the output layer of a binary classification neural network? Sigmoid Sigmoid ReLU ReLU Tanh Tanh Softmax Softmax Linear Linear Download as PDFRelated posts:Big Data MCQsBlock Chain MCQsCloud Computing MCQsComputer Networks MCQs#6. What is a hyperparameter in machine learning? A parameter set prior to training and remains constant during training A parameter set prior to training and remains constant during training A parameter that determines the number of features in the dataset A parameter that determines the number of features in the dataset A parameter learned by the model during training A parameter learned by the model during training A parameter that determines the number of training samples A parameter that determines the number of training samples A parameter that is only relevant for unsupervised learning A parameter that is only relevant for unsupervised learning #7. In which phase of the machine learning process is feature engineering typically performed? Data preprocessing Data preprocessing Model training Model training Model evaluation Model evaluation Model deployment Model deployment Data collection Data collection #8. Which algorithm is used for dimensionality reduction in machine learning? Principal Component Analysis (PCA) Principal Component Analysis (PCA) Random Forest Random Forest K-Nearest Neighbors (KNN) K-Nearest Neighbors (KNN) Gradient Descent Gradient Descent Support Vector Machine (SVM) Support Vector Machine (SVM) #9. What is the purpose of regularization in machine learning? To prevent overfitting To prevent overfitting To increase the complexity of the model To increase the complexity of the model To decrease the complexity of the model To decrease the complexity of the model To speed up the training process To speed up the training process To add noise to the data To add noise to the data #10. Which evaluation metric is commonly used for regression problems in machine learning? Mean Absolute Error (MAE) Mean Absolute Error (MAE) Accuracy Accuracy F1-score F1-score Precision Precision Recall Recall Download as PDFRelated posts:Big Data MCQsBlock Chain MCQsCloud Computing MCQsComputer Networks MCQs#11. Which algorithm is used for anomaly detection in machine learning? Isolation Forest Isolation Forest Logistic Regression Logistic Regression K-Means Clustering K-Means Clustering Decision Trees Decision Trees Support Vector Machines (SVM) Support Vector Machines (SVM) #12. What is the purpose of the bias term in a neural network? To shift the activation function to the left or right To shift the activation function to the left or right To reduce overfitting To reduce overfitting To increase model complexity To increase model complexity To regularize the model To regularize the model To add non-linearity To add non-linearity #13. What is the goal of unsupervised learning? Discovering hidden patterns or structures in data Discovering hidden patterns or structures in data Maximizing prediction accuracy Maximizing prediction accuracy Minimizing model complexity Minimizing model complexity Minimizing training time Minimizing training time Classifying data into predefined categories Classifying data into predefined categories #14. Which method is commonly used to handle missing data in a dataset? Imputation Imputation Deletion Deletion Ignoring it during training Ignoring it during training Normalization Normalization Standardization Standardization #15. What is the purpose of the Adam optimizer in deep learning? A stochastic gradient descent optimization algorithm A stochastic gradient descent optimization algorithm A clustering algorithm A clustering algorithm A dimensionality reduction technique A dimensionality reduction technique A regularization technique A regularization technique A feature extraction method A feature extraction method Download as PDFRelated posts:Big Data MCQsBlock Chain MCQsCloud Computing MCQsComputer Networks MCQs#16. In reinforcement learning, what is the agent's objective? To maximize the cumulative reward over time To maximize the cumulative reward over time To minimize the cumulative reward over time To minimize the cumulative reward over time To memorize the training data To memorize the training data To predict future states To predict future states To classify data into predefined categories To classify data into predefined categories #17. Which technique is used to reduce the risk of overfitting in decision trees? Pruning Pruning Grafting Grafting Bagging Bagging Boosting Boosting Random selection of features Random selection of features #18. What does the term "bias-variance tradeoff" refer to in machine learning? The balance between model complexity and the amount of training data The balance between model complexity and the amount of training data The balance between underfitting and overfitting The balance between underfitting and overfitting The tradeoff between the accuracy of a model and its interpretability The tradeoff between the accuracy of a model and its interpretability The tradeoff between bias (error due to too simple model) and variance (error due to too complex model) The tradeoff between bias (error due to too simple model) and variance (error due to too complex model) The tradeoff between the number of features and the number of samples in the dataset The tradeoff between the number of features and the number of samples in the dataset #19. What is the purpose of a confusion matrix in classification problems? To visualize the performance of a model To visualize the performance of a model To display the distribution of classes in a dataset To display the distribution of classes in a dataset To evaluate the quality of features To evaluate the quality of features To quantify the performance of a classification model To quantify the performance of a classification model To calculate the probability of class membership To calculate the probability of class membership #20. Which algorithm is commonly used for collaborative filtering in recommendation systems? Matrix Factorization Matrix Factorization K-Nearest Neighbors (KNN) K-Nearest Neighbors (KNN) Support Vector Machines (SVM) Support Vector Machines (SVM) Decision Trees Decision Trees Random Forest Random Forest Download as PDFRelated posts:Big Data MCQsBlock Chain MCQsCloud Computing MCQsComputer Networks MCQsNextResults Download as PDFRelated posts:Big Data MCQsBlock Chain MCQsCloud Computing MCQsComputer Networks MCQs Download as PDFRelated posts:Big Data MCQsBlock Chain MCQsCloud Computing MCQsComputer Networks MCQs Download as PDFShare this:Click to share on Facebook (Opens in new window)Click to share on Telegram (Opens in new window)Click to share on WhatsApp (Opens in new window)Related posts:Big Data MCQsBlock Chain MCQsCloud Computing MCQsComputer Networks MCQs