Confusion Matrix Explained Clearly | TP, FP, FN, TN | Accuracy, Precision, Recall, F1 Score
Автор: ZeroToQuery
Загружено: 2026-01-11
Просмотров: 5
Confusion Matrix is one of the most important evaluation tools in Machine Learning, especially for Logistic Regression and classification problems.
In this video, we explain Confusion Matrix step by step, using real-life examples like medical diagnosis, spam detection, and fraud detection. You will clearly understand:
✔ What is a Confusion Matrix
✔ True Positive, True Negative, False Positive, False Negative
✔ How Accuracy, Precision, Recall, and F1 Score are calculated
✔ When to use Precision vs Recall
✔ Why Accuracy can be misleading in imbalanced datasets
✔ Interview-ready explanations with intuition
This video is perfect for:
Machine Learning beginners
Data Science students
Interview preparation
Exam preparation
📌 No heavy math – pure intuition and clarity.
If you find this video helpful, don’t forget to like, share, and subscribe 😊
#ConfusionMatrix
#MachineLearning
#DataScience
#LogisticRegression
#PrecisionRecall
#F1Score
#Classification
#MLBeginners
#DataScienceInterview
#AI
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