A data scientist is attempting to tune a logistic regression model logistic using scikit-learn. They want to specify a search space for two hyperparameters and let the tuning process randomly select values for each evaluation.
They attempt to run the following code block, but it does not accomplish the desired task:
Which of the following changes can the data scientist make to accomplish the task?
A data scientist is using MLflow to track their machine learning experiment. As a part of each of their MLflow runs, they are performing hyperparameter tuning. The data scientist would like to have one parent run for the tuning process with a child run for each unique combination of hyperparameter values. All parent and child runs are being manually started with mlflow.start_run.
Which of the following approaches can the data scientist use to accomplish this MLflow run organization?
A data scientist uses 3-fold cross-validation when optimizing model hyperparameters for a regression problem. The following root-mean-squared-error values are calculated on each of the validation folds:
• 10.0
• 12.0
• 17.0
Which of the following values represents the overall cross-validation root-mean-squared error?
A machine learning engineer is trying to scale a machine learning pipelinepipelinethat contains multiple feature engineering stages and a modeling stage. As part of the cross-validation process, they are using the following code block:
A colleague suggests that the code block can be changed to speed up the tuning process by passing the model object to theestimatorparameter and then placing the updated cv object as the final stage of thepipelinein place of the original model.
Which of the following is a negative consequence of the approach suggested by the colleague?
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