Machine Learning 2-Ms. Mona

In a decision tree, what is a leaf node?

• Data visualization  

• Predictive modeling

• Software development 

• Hardware optimization

What is the area under the Receiver Operating Characteristic (ROC) curve used to measure?

• Classification accuracy  

• Precision

• Sensitivity and specificity  

• Mean Squared Error (MSE) 

is a feedback-based learning method, in which a learning agent gets a reward for each right action and gets a penalty for each wrong action.

• 1. Reinforcement learning 

• 2. Supervised learning 

• 3. Unsupervised learning  

• 4. All of above 

What is the role of a hyperparameter in machine learning?

• Feature selection

• Model parameter adjustment during training

• Data preprocessing

• Cross-validation

Which type of learning algorithm does not require labeled training data?

• Supervised learning

• Unsupervised learning

• Semi-supervised learning

• Reinforcement learning

Which algorithm is commonly used for clustering in unsupervised learning?

• Support Vector Machine (SVM)

• K-Nearest Neighbors (KNN)

• K-Means

• Decision Tree

Which algorithm is commonly used for regression tasks in machine learning?

• K-Means

• Decision Tree

• Random Forest

• Linear Regression

What is the purpose of regularization in machine learning?

• Reduce model complexity to prevent overfitting

• Increase model complexity to improve accuracy

• Speed up the training process

• Normalize input features

What is the primary goal of machine learning?

• Data visualization

• Predictive modeling

• Software development

• Hardware optimization

What is the purpose of the training-validation-test split in machine learning?

• Increase model complexity

• Evaluate model performance on unseen data

• Decrease training time

• Ensure feature scaling