In the above snap from the week 3 optional lab on logistic regression, where i have added more points to the training data. I see that the logistic regression still mis-classifies certain points. does this not make the logistic regression fail when classifying this kind of data just like linear regression which fails when a point too farther is added?
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Which additional points did you add?
the crosses and circles you may see in the attached figure.
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Hello @AzharAli, yes, logistic regression model can make wrong prediction.
While linear regression model is a line in the features space so that outliners will get pretty bad predictions, logistic regression model is a hyperplane in the features space so that False (benign) samples that cross the hyperplane and locate inside the cluster of True (malignant) samples would be easily mispredicted.
Cheers,
Raymond
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In general all models output an answer with a probability below 100%, so there are always cases when the model fails!
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