A data scientist learned during their training to always use 5-fold cross-validation in their model development workflow. A colleague suggests that there are cases where a train-validation split could be preferred over k-fold cross-validation when k > 2.Which of the following describes a potential benefit of using a train-validation split over k-fold cross-validation in this scenario?
Which of the following hyperparameter optimization methods automatically makes informed selections of hyperparameter values based on previous trials for each iterative model evaluation?
A team is developing guidelines on when to use various evaluation metrics for classification problems. The team needs to provide input on when to use the F1 score over accuracy.Which of the following suggestions should the team include in their guidelines?
A data scientist has developed a random forest regressor rfr and included it as the final stage in a Spark MLPipeline pipeline. They then set up a cross-validation process with pipeline as the estimator in the following code block:Which of the following is a negative consequence of including pipeline as the estimator in the cross-validation process rather than rfr as the estimator?
A data scientist has written a feature engineering notebook that utilizes the pandas library. As the size of the data processed by the notebook increases, the notebook's runtime is drastically increasing, but it is processing slowly as the size of the data included in the process increases.Which of the following tools can the data scientist use to spend the least amount of time refactoring their notebook to scale with big data?
A data scientist has developed a linear regression model using Spark ML and computed the predictions in a Spark DataFrame preds_df with the following schema: prediction DOUBLE actual DOUBLEWhich of the following code blocks can be used to compute the root mean-squared-error of the model according to the data in preds_df and assign it to the rmse variable?
