The problem could be rectified by introducing a threshold such that when the predicted y is greater than the threshold, we classify y as 1. This become the most simple neural network model, which will be introduced later.
{"Image DocumentName": "The problem could be rectified by introducing a threshold such that when the predicted y is greater than the threshold, we classify y as 1. This become the most simple neural network model, which will be introduced later.", "Image ImageDescription": "However, what we obtain become a decision rather than a probability, which might be useful in some cases. Also, the relation between the probability and the explanatory variable become less clear. Statisticians invented logistic regression to solve the problem.", "Image XResolution": "37", "Image YResolution": "37", "Image ResolutionUnit": "Pixels/Centimeter", "Image Software": "SlidePlayer", "Image YCbCrPositioning": "Centered"}