Generate a Confusion Matrix for Binary Classification

Task: Generate a Confusion Matrix

Your task is to implement the function confusion_matrix(data) that generates a confusion matrix for a binary classification problem. The confusion matrix provides a summary of the prediction results on a classification problem, allowing you to visualize how many data points were correctly or incorrectly labeled.

Input:

• A list of lists, where each inner list represents a pair
• [y_true, y_pred] for one observation. y_true is the actual label, and y_pred is the predicted label.

Output:

• A $2 \times 2$ confusion matrix represented as a list of lists.

from collections import Counter

def confusion_matrix(data):
	# Implement the function here
	pass