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What is ‘model tuning’?
A. Adjusting hyperparameters to improve model performance
B. Creating new features from existing data
C. Reducing the dimensionality of the data
D. Scaling features to a common range
Answer: Adjusting hyperparameters to improve model performance
What does ‘out-of-bag’ error refer to?
A. The error estimate obtained using observations not included in the bootstrap sample during model training
B. The error due to missing values in the dataset
C. The error due to feature scaling
D. The error due to dimensionality reduction
Answer: The error estimate obtained using observations not included in the bootstrap sample during model training
Which of the following is a ‘tree-based’ model?
A. Decision Trees
B. K-Nearest Neighbors (KNN)
C. Principal Component Analysis (PCA)
D. Naive Bayes
Answer: Decision Trees
Which algorithm is used for ‘probabilistic’ classification?
A. Naive Bayes
B. Support Vector Machine (SVM)
C. K-Nearest Neighbors (KNN)
D. Decision Trees
Answer: Naive Bayes
What is ‘self-supervised learning’?
A. A type of machine learning where the model generates labels from the data itself
B. A technique for feature scaling
C. A method for dimensionality reduction
D. A type of unsupervised learning
Answer: A type of machine learning where the model generates labels from the data itself
Which of the following is a method for evaluating classification models?
A. Confusion Matrix
B. Principal Component Analysis (PCA)
C. K-means Clustering
D. Feature Scaling
Answer: Confusion Matrix
Which of the following is an example of a ‘generative’ model?
A. Generative Adversarial Network (GAN)
B. Support Vector Machine (SVM)
C. Linear Regression
D. K-Nearest Neighbors (KNN)
Answer: Generative Adversarial Network (GAN)
What does ‘autoencoder’ do?
A. A neural network used for unsupervised learning tasks, including dimensionality reduction
B. A technique for scaling features
C. A method for feature selection
D. A type of supervised learning algorithm
Answer: A neural network used for unsupervised learning tasks, including dimensionality reduction
What does ‘deep learning’ refer to?
A. A subset of machine learning involving neural networks with multiple layers
B. A technique for clustering data points
C. A method for handling missing values
D. A technique for dimensionality reduction
Answer: A subset of machine learning involving neural networks with multiple layers