GMLE 試験問題を無料オンラインアクセス

What is the main advantage of using a 'bagging' approach in ensemble learning?
Response:

• A.To increase the bias in the model
• B.To reduce the variance of the model
• C.To enhance the speed of training models
• D.To optimize individual model parameters

Which of the following is a supervised learning algorithm commonly used for classification tasks?
Response:

• A.Support Vector Machines (SVM )
• B.Agglomerative clustering
• C.k-means
• D.Principal Component Analysis (PCA)

Which techniques can be used to improve the performance of a linear regression model?
(Choose two)
Response:

• A.Increasing the number of decision trees
• B.Adding regularization, such as L1 (Lasso) or L2 (Ridge)
• C.Including interaction terms between variables
• D.Reducing the dataset size

What is NumPy essential for in data science?
Response:

• A.Handling large arrays and matrices efficiently
• B.Web scraping and data collection
• C.Text processing and natural language understanding
• D.Building interactive dashboards

How does 'L1 regularization' differ from 'L2 regularization' in machine learning?
Response:

• A.L1 adds the absolute value of coefficients; L2 adds the square of coefficients
• B.L1 is used for regression; L2 is used for classification
• C.L1 is for neural networks; L2 is for decision trees
• D.L1 optimizes the learning rate; L2 optimizes the batch size