What's wrong with my code?

$$I Got the following feedback :

"Test Failed: The SVM classifier evaluation metrics are not found because evaluate$\_$svm$\_$classifier function is not implemented or not working as intended."

In $[4]$: from sklearn.svm import SVC

from sklearn.neighbors import KNeighborsClassifier

from sklearn.metrics import accuracy$\_$score, precision$\_$score, recall$\_$score, confusion$\_$matrix

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

evaluate$\_$svm$\_$classifier $=$ SVC$($kernel $=$ 'lin$$ar$\text{'})$

evaluate$\_$svm$\_$classifier.fit$($X$\_$train, y$\_$train$)$

y$\_$pred $=-$evaluate$\_$svm$\_$classifier.predict$($X$\_$test$)$

precision $=$ precision$\_$score $($y$\_$test, y$\_$pred$)$

recall $=$ recall$\_$score $($y$\_$test, y$\_$pred$)$

accuracy $=$ accuracy$\_$score $($y$\_$test, y$\_$pred$)$

slope $=$ evaluate$\_$svm$\_$classifier.coef$\_[0][0]/$ evaluate$\_$svm$\_$classifier.coef$\_[0][1]$

intercept $=-$ ev$\backslash$bar $($a$)$ lu$\backslash$bar $($a$)$ e$\_$svm$\_$classifi$$r$.$intercept$\_[0]/$valuate$\_$svm$\_$classifier.coef$\_[0][1]$

false$\_$positives, false$\_$negatives $=$ confusion$\_$matrix$($y$\_$test, y$\_$pred$).$ravel$()$

$"""$

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