Logistic regression optional lab

Course Q&A Machine Learning Specialization Supervised ML: Regression and Classification
1

Hello there,

I am facing a problem to understand something, in the first optional lab of week 3 it says that linear regression fails to correctly classify points and thus comes the need for logistic regression.

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In the second lab I cannot understand what the orange line means, it seems its the original linear regression model, however, it correctly classifies the points even after adding the point at x = 10

the notes say: β€œNote, the orange line is β€˜π‘§β€™ or 𝐰⋅𝐱(𝑖)+𝑏 above. It does not match the line in a linear regression model.” but i cannot get what this means.

thanks in advance

2

Hello @Omar_Atef_ElGedawy, yes - the orange is the linear regression model z = 4.79 - 11.77 and the blue line is the logistic regression model y = sigmoid(z) as the legend explains. What’s your concern about this?

Raymond