$1,1$ point

$[$Prompt $1]$ In the following exercise, the Boston dataset contains $14$ columns, each with $506$ observations. Consider the following piece of code. You may want to run the code on

a separate Python notebook, although not necessary to complete this exercise.

$[$Refer to Prompt $1]$ What will the following piece of code produce?

$1$ print$("$Length of $y_{-}$train: $",$ len$($y$\_$train$))$

Length of y$\_$train: $404$

Length of y$\_$train: $506$

Length of $y_{-}$train: $13$

Length of $y_{-}$train: $102$

Length of $y_{-}$train: $5252$

$1$ point

$[$Refer to Prompt $1]$ What will the following piece of code produce?

$1$ print$("$Length of $x\_$test: $",$ len$($X$\_$test$))$

Length of $x\_$test: $404$

Length of $x\_$test: $506$

Length of $x\_$test: $13$

Length of $x$ test: $102$

Length of X$\_$test: $5252$

$1$ point

$[$Refer to Prompt $1]$ What will the following piece of code produce?

$1$ print$("$Length of test: $",$ len$($y$\_$test$))$

Length of $y_{-}$test: $404$

Length of $y_{{?}_t\text{e}\text{s}\text{t}\text{:}}^{506}$

Length of $y$ test: $13$

Length of $y_{{?}_t\text{e}\text{s}\text{t}\text{:}102}$

Length of $y\_$test: $5252$

$[$Refer to Prompt $1]$ In the following piece of code, the random$\_$state parameter allows us to shuffle the data in the Boston dataset in a way that is reproducible. Which of the

following is true?

$1kf=$ KFold$($n$\_$splits $=11,$ random$\_$state $=42,$ shuffle $=$ True$)$

$2$ for train$\_$index, test$\_$index in $kf.$split$(x$ :

$3$ print$("$TRAIN:$",$ train$\_$index, "TEST:", test$\_$index$)$

$4$ print$($len$($train$\_$index$))$

$5$ print$($len$($test$\_$index$))$

The code will run cross validation a total of $11$ times $($loops$).$ In each loop, the code will separate the dataset into $460$ observations of training data $($train$\_$index$)$ and $46$

observations of testing data $($test$\_$index$).$

The code will run cross validation a total of $11$ times $($loops$).$ In each loop, the code will separate the dataset into $464$ observations of training data $($train index$)$ and $42$

observations of testing data $($test$\_$index$).$

The code will run cross validation a total of $42$ times $($loops$).$ In each loop, the code will separate the dataset into $494$ observations of training data $($train index$)$ and $12$

observations of testing data $($test$\_$index$)$

The code will run cross validation a total of $14$ times $($loops$).$ In each loop, the code will separate the dataset into $506$ observations of training data $($train$\_$index$)$ and $506$

observations of testing data $($test$\_$index$).$

The code will run cross validation a total of $13$ times $($loops$).$ In each loop, the code will separate the dataset into $460$ observations of training data $($train index$)$ and $46$

observations of testing data $($test$\_$index$).$

$[$Refer to Prompt $1]$ If we wish to implement Leave$-$One$-$Out$-$Cross$-$Validation $($LOOCV$),$ the value of the parameter n$\_$splits in the function KFold $($see the previous question

would be $\_\_.($Answer should be a whole number.$)$

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