In $[]$: def evaluate$\_$svm$\_$classifier$($X$\_$train, y$\_$train, X$\_$test, y$\_$test$)$:

$".""$

Trains an SVM classifier with a linear kernel on the training set and evaluates its performance on the test set.

Parameters:

X$\_$train: Training data features.

y$\_$train: Training data labels.

X$\_$test: Test data features.

y$\_$test: Test data labels.

Returns:

Slope and intercept of the decision boundary.

Accuracy, precision, recall on the test set.

Number of false positives and false negatives.

$""."$

return slope, intercept, accuracy, precision, recall, false$\_$positives, false$\_$negatives

# Usage example :

# slope, intercept, accuracy, precision, recall, false$\_$positives, false$\_$negatives $=$ evaluate$\_$svm$\_$classifier$($X$\_$train, y$\_$train, X$\_$t

# print$($f$"$Slope: $\{$slope$\},$ Intercept: $\{$intercept$\},$ Accuracy: $\{$accuracy$\},$ Precision: $\{$precision$\},$ Recall: $\{$recall$\},$ False Positives