Which of the following statements about model fitting and fine tuning is most accurate?Group of answer choicesFine tuning is also often called “model estimation”A model’s hyperparameters are learned by fitting the model to the training dataFine tuning is based on a trial-and-error systemThe model’s in-sample performance is estimated during fine tuning

Question 2Complete the following sentence: The training data is used to fit the model, while the test data is used to:1 pointmeasure the parameters and hyperparameters of the modeltweak the model hyperparameterstweak the model parametersmeasure error and performance of the model

Accuracy is always the primary metrics that is used to measure a model’s performance.

Which of the following best describes the order of the 3-way split for model validation when fine-tuning of hyperparameters?Group of answer choicesValidation set; Training set; Test setTraining set; Validation set; Test setTraining set; Test set; Validation setTest set; Training set; Validation set

Question 3What’s the correct order for using a model? 1 pointSplit the data into training and test sets, fit the model on the train set, evaluate model accuracy.Clean the data, split the data into training and test sets, fit the model on the train set, evaluate model accuracy.Split the data into the training and test sets, fit the model on the train set, clean the data, evaluate model accuracy.Clean the data, fit the model on the entire dataset, split the data into training and test sets, evaluate model accuracy.

The fine tuning argument is an inference to the best explanation argument. Group of answer choicesTrueFalse