TDSM 9.7

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9.7.png

Let's discuss 3 cases, c=0.1, 1 and 10.

According to the graph, 1) if c=0.1, the logit function give probabilities which differ little. Therefore, the model like logistic regression might not be able to distinguish the observation which has similar units.

2) if c=1, the logit function gives fair distribution.

3) if c=10, the logit function would converge to 0 or 1 too fast that the model could not tolerate errors.