write a python code for the following

Objective:

Train an SVM classifier with a linear kernel on the training dataset.

Evaluate the classifier's performance on the test dataset.

Return the slope and intercept of the decision boundary, along with key performance metrics: accuracy, precision, recall, false positives, and false negatives.

Requirements:

Implement a function named evaluate$\_$svm$\_$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.

SVM Kernel should be linear

Return:

Slope and intercept of the decision boundary.

Accuracy, precision, recall of the classifier on the test set.

Number of false positives and false negatives.