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Classification accuracy confusion_matrix_middleschool
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- 2. AI Club Classification Accuracy andConfusion Matrix
- 3. How do youmeasure how good a Model is? • Create a “Validation Dataset” – a part of the training data put aside to test • Validation dataset has the actual (correct answer) • After model is trained, use it to predict the answer and compare prediction to the actual answer in the validation dataset
- 4. How to MeasureClassification • In classification, answer is precisely right or wrong. Right if it matches label, wrong otherwise (no matter how many categories there are) • Accuracy • Correct Answers*100/Total answers • Closer to 100% the better • We will see more metrics in later projects Number of Countries Visited Number of Years in School Height (Feet) Original Label Who am I? What the model predicted 15 13 5.0 Adult Adult 2 3 3.5 Child Child 7 4 4.0 Child Child 1 5 7.0 Adult Child 3 Correct * 100/ 4 Total = 75%
- 5. What is the Accuracy? TrueLabel Predicted Value Adult Adult Adult Child Child Adult Adult Child Child Child Child Child Child Adult Adult Adult Child Child Adult Adult
- 6. What is the Accuracy? 60% TrueLabel Predicted Value Adult Adult Adult Child Child Adult Adult Child Child Child Child Child Child Adult Adult Adult Child Child Adult Adult
- 7. What is the Accuracy? TrueLabel Predicted Value Child Child Child Child Child Child Adult Child Child Child Child Child Child Child Adult Child Child Child Child Child
- 8. True Label PredictedValue Child Child Child Child Child Child Adult Child Child Child Child Child Child Child Adult Child Child Child Child Child What is the Accuracy? 80%
- 9. What did younotice? •In table 2, a dumb algorithm that predicts only one value has a high accuracy.
- 10. What did younotice? •In table 2, a dumb algorithm that predicts only one value has a high accuracy. •Accuracy value is not enough to measure the performance of an algorithm •We need other ways to understand if an algorithm is good or bad
- 11. Create a confusionmatrix Fill the below with the counts That’s your confusion matrix. It tells you how confused your algorithm is! Child Adult Child Adult PREDICTIONS LABELS True Label Predicted Value Adult Adult Adult Child Child Adult Adult Child Child Child Child Child Child Adult Adult Adult Child Child Adult Adult
- 12. Create a confusionmatrix Fill the below with the counts How many times did the algorithm predict Adult and was right about it? Child Adult Child Adult PREDICTIONS LABELS True Label Predicted Value Adult Adult Adult Child Child Adult Adult Child Child Child Child Child Child Adult Adult Adult Child Child Adult Adult
- 13. Create a confusionmatrix Fill the below with the counts That’s your confusion matrix. It tells you how confused your algorithm is! Child Adult Child Adult PREDICTIONS LABELS True Label Predicted Value Adult Adult Adult Child Child Adult Adult Child Child Child Child Child Child Adult Adult Adult Child Child Adult Adult
- 14. Create a confusionmatrix Fill the below with the counts That’s your confusion matrix. It tells you how confused your algorithm is! Child Adult Child Adult PREDICTIONS LABELS True Label Predicted Value Adult Adult Adult Child Child Adult Adult Child Child Child Child Child Child Adult Adult Adult Child Child Adult Adult 3
- 15. Create a confusionmatrix Fill the below with the counts How many times did the algorithm predict Child and was right about it? Child Adult Child Adult PREDICTIONS LABELS True Label Predicted Value Adult Adult Adult Child Child Adult Adult Child Child Child Child Child Child Adult Adult Adult Child Child Adult Adult 3
- 16. Create a confusionmatrix Fill the below with the counts How many times did the algorithm predict Child and was right about it? Child Adult Child Adult PREDICTIONS LABELS True Label Predicted Value Adult Adult Adult Child Child Adult Adult Child Child Child Child Child Child Adult Adult Adult Child Child Adult Adult 3 3
- 17. Create a confusionmatrix Fill the below with the counts How many times did the algorithm predict Child and was wrong about it? Child Adult Child Adult PREDICTIONS LABELS True Label Predicted Value Adult Adult Adult Child Child Adult Adult Child Child Child Child Child Child Adult Adult Adult Child Child Adult Adult 3 3
- 18. Create a confusionmatrix Fill the below with the counts How many times did the algorithm predict Child and was wrong about it? Child Adult Child Adult PREDICTIONS LABELS True Label Predicted Value Adult Adult Adult Child Child Adult Adult Child Child Child Child Child Child Adult Adult Adult Child Child Adult Adult 3 3 2
- 19. Create a confusionmatrix Fill the below with the counts How many times did the algorithm predict Adult and was wrong about it? Child Adult Child Adult PREDICTIONS LABELS True Label Predicted Value Adult Adult Adult Child Child Adult Adult Child Child Child Child Child Child Adult Adult Adult Child Child Adult Adult 3 3 2
- 20. Create a confusionmatrix Fill the below with the counts How many times did the algorithm predict Adult and was wrong about it? Child Adult Child Adult PREDICTIONS LABELS True Label Predicted Value Adult Adult Adult Child Child Adult Adult Child Child Child Child Child Child Adult Adult Adult Child Child Adult Adult 3 3 2 2
- 21. Create a confusionmatrix That’s your confusion matrix. It tells you how confused your algorithm is! Child Adult Child Adult PREDICTIONS LABELS 3 3 2 2 •How can you calculate Accuracy from your confusion Matrix?
- 22. Create a confusionmatrix That’s your confusion matrix. It tells you how confused your algorithm is! Child Adult Child Adult PREDICTIONS LABELS 3 3 2 2 •Accuracy = sum(Diagonal Values)x100/ Total = (3+3)x100/(3+3+2+2) = 60% •How can you calculate Accuracy from your confusion Matrix?
- 23. Exercise - 5 Calculateaccuracy using the confusion matrix Child Adult Child Adult PREDICTIONS LABELS 3 3 2 2 Child Adult Child Adult PREDICTIONS LABELS 0 8 0 2
- 24.