LAB

$1\mathrm{.}6\mathrm{.}1$: LAB: Model workflow in scikit$-$learn

The dataset fg$\_$attempts.csv contains data on field goal distance and outcome $($whether or not the kick was successful$)$ during the

$2012$ NFL seasons.

Create a dataframe X with input features Distance and ScoreDiffPreKick.

Create a dataframe y with output feature outcome.

Flatten y into an array called yArray using np$.$ravel $().$

Initialize a logistic regression model using LogisticRegression$().$

Fit the model to the input and flattened output features in X and yArray $.$

Create a new dataframe XNew with user$-$input values for Distance and ScoreDiffPreKick.

Use the fitted logistic regression model to predict the outcome from the new data.

Determine the accuracy of a fitted logistic regression classification model.

Ex: If the new dataframe contains Distance $=25$ and ScoreDiffPreKick $=8,$ the program input is:

$25$

$8$

and the program output is:

$[1]$

$0\mathrm{.}8604651162790697$