write a python code for these requirements,

Objective:

Use the KNN classifier to make predictions on a test dataset.

Evaluate the classifier's performance using metrics such as accuracy, precision, recall, true positives, and true negatives.

$2\mathrm{.}1\mathrm{.}4\mathrm{.}1$ Requirements:

Implement a function named evaluate$\_$knn$\_$classifier.

Parameters:

x$\_$train : Training data features as a numpy array.

y$\_$train : Training data labels as a numpy array.

x$\_$test : Test data features as a numpy array.

y$\_$test : Test data labels as a numpy array.

best$\_$k: The optimal number of neighbors as an integer. This should be taken from the output of last function.

Return:

The function should return the evaluation metrics for the test set: accuracy, precision, recall, true positives, and true negatives.