Is it possible to test for the probability of improving model accuracy without cross-validation techniques? If yes, please explain.

4 years ago
Machine Learning

Yes, it is possible to test for the probability of improving model accuracy without cross-validation techniques. We can do so by running the ML model for say n number of iterations, recording the accuracy. Plot all the accuracies and remove the 5% of low probability values. Measure the left [low] cut off and right [high] cut off. With the remaining 95% confidence, we can say that the model can go as low or as high [as mentioned within cut off points]. 

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Sanisha Maharjan
Sanisha Maharjan
Jan 11, 2022
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