$1$

$((($ Do it in python $)))$

Requirements:

The function should be named create$\_$and$\_$train$\_$knn$\_$model $.$

Parameters:

X$\_$train : A $2$D array of the training features.

y$\_$train : A $1$D array of the training labels.

$k$ : An integer representing the number of neighbors to consider. The default value

should be $1.$

Return:

The function should return the trained KNN model, which is trained onn the input

training data and with the input value of $k.$

In $[]$: def create$\_$and$\_$train$\_$knn$\_$model$($x$\_$train, y$\_$train, $k=1)$:

$"""$

Creates and trains a K$-$Nearest Neighbors $($KNN$)$ model.

Parameters:

X$\_$train: $2$D array of training features.

y$\_$train: $1$D array of training labels.

$k$ : Integer, number of neighbors $($default: $1).$

Returns:

Trained KNN model.

$"""$

# Initialize the KNN model with $k$ neighbors

# Train the model with X$\_$train and y$\_$train

# Return the trained model

return model

# Example usage:

# model $=$ create$\_$and$\_$train$\_$knn$\_$model$($X$\_$train, y$\_$train, $k=5$