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Which type of neural network is best suited for sequential data?
A. Recurrent Neural Network (RNN)
B. Convolutional Neural Network (CNN)
C. Generative Adversarial Network (GAN)
D. Feedforward Neural Network
Answer: Recurrent Neural Network (RNN)
In a decision tree, what does a ‘leaf node’ represent?
A. A terminal node that represents a classification or regression outcome
B. A node that splits the data based on a feature
C. A node that holds the root of the tree
D. A node used for data preprocessing
Answer: A terminal node that represents a classification or regression outcome
Which of the following is a technique for feature selection?
A. Recursive Feature Elimination (RFE)
B. Principal Component Analysis (PCA)
C. K-means Clustering
D. Support Vector Machines (SVM)
Answer: Recursive Feature Elimination (RFE)
What does the term ‘ensemble learning’ refer to?
A. Combining predictions from multiple models to improve accuracy
B. Training a single model on different datasets
C. Optimizing a model's hyperparameters
D. Visualizing the data
Answer: Combining predictions from multiple models to improve accuracy
Which of the following techniques is used to balance an imbalanced dataset?
A. Cross-validation
B. Data Augmentation
C. Resampling
D. Feature Scaling
Answer: Resampling
In the context of machine learning, what is ‘bagging’?
A. A method for combining multiple models to improve accuracy
B. A technique for data preprocessing
C. A method for feature selection
D. A type of neural network architecture
Answer: A method for combining multiple models to improve accuracy
Which algorithm is commonly used for regression tasks?
A. K-means Clustering
B. Support Vector Machine (SVM)
C. Linear Regression
D. Principal Component Analysis (PCA)
Answer: Linear Regression
Which of the following is a type of neural network used for image recognition?
A. Convolutional Neural Network (CNN)
B. Recurrent Neural Network (RNN)
C. Generative Adversarial Network (GAN)
D. Feedforward Neural Network
Answer: Convolutional Neural Network (CNN)
What is a confusion matrix used for?
A. To evaluate the performance of a classification model
B. To perform dimensionality reduction
C. To measure the similarity between data points
D. To optimize the model's parameters
Answer: To evaluate the performance of a classification model