GMLE 試験問題を無料オンラインアクセス

You are building a multiple linear regression model to predict employee salaries based on years of experience, education level, and performance ratings. After training the model, you notice that it is overfitting the training data.
What techniques should you use to reduce overfitting and improve the model's generalization?
Response:

• A.Focus only on the most recent data and ignore the training set
• B.Remove regularization and increase the number of training samples
• C.Apply L2 regularization (Ridge), reduce the complexity of the model, and increase the size of the training dataset
• D.Increase the number of features and training epochs

What is the primary use of 'k-fold cross-validation' in machine learning?
Response:

• A.To increase the size of the training dataset
• B.To select the most important features of the dataset
• C.To optimize the hyperparameters of the model
• D.To assess the model's performance on different subsets of the data

You are tasked with collecting data from an external API for use in a machine learning model. After making several requests, you notice that the data contains missing values and inconsistencies across different records. What steps should you take to clean and prepare this data for further analysis and modeling?
Response:

• A.Identify and remove records with missing values, apply data normalization techniques, and ensure data consistency before model training
• B.Ignore the inconsistencies and proceed directly to model training
• C.Focus on fixing inconsistencies only in the training data, ignoring the test data
• D.Collect additional data from a different source without fixing the original dataset

What is the main purpose of the latent space in an autoencoder?
Response:

• A.To store weights for model training
• B.To serve as a compressed representation of the input data
• C.To classify anomalies directly
• D.To generate labels for the dataset

What does the term 'epoch' refer to in the context of training a deep learning model?
Response:

• A.The final phase of model training
• B.The initial phase of model training
• C.A single iteration over the entire dataset
• D.The process of tuning hyperparameters