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Give an example where High Accuracy is not usable. 

Topic - Evaluation

Type - Short answer 

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Let us go back to the Forest Fire example. Assume that the model always predicts that there is no fire.

But in reality, there is a 2% chance of forest fire breaking out. In this case, for 98 cases, the model will be right but for those 2 cases in which there was a forest fire, then too the model predicted no fire.


Here, 

  • True Positives = 0 
  • True Negatives = 98 
  • Total cases = 100 
  • Therefore, accuracy becomes: (98 + 0) / 100 = 98%

This is a fairly high accuracy for an AI model. 

But this parameter is useless for us as the actual cases where the fire broke out are not taken into account. 

Hence, there is a need to look at another parameter which takes account of such cases as well known as precision.


Study more about Evaluation at Evaluation Class 10

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SCENARIO: An expensive robotic chicken crosses a very busy road a thousand times per day. An ML model evaluates traffic patterns and predicts when this chicken can safely cross the street with an accuracy of 99.99%.

Explanation: A 99.99% accuracy value on a very busy road strongly suggests that the ML model is far better than chance. In some settings, however, the cost of making even a small number of mistakes is still too high. 99.99% accuracy means that the expensive chicken will need to be replaced, on average, every 10 days. (The chicken might also cause extensive damage to cars that it hits.)


Study more about Evaluation at Evaluation Class 10

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