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mrdbourke / pytorch-deep-learning

Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
https://learnpytorch.io
MIT License
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Evaluation of Model #742

Open kumarsiddappa-git opened 9 months ago

kumarsiddappa-git commented 9 months ago

Hi All ,

Wanted to understand , when we evaluate using the plot_decision_boundary. But how do we test the model apart from it.

Do we give the new test values to the model and then plot it again , would this steps followed in real world?

Can we have on session explaining the plot_decision_boundary module.

Thanks Kumar.S

kumarsiddappa-git commented 9 months ago

In the moon_cirlce or circle , Y indicates the label weather its red or blue, but what does the columns in the X indicates ? if we are using linear regression , the X has two columns which are X1 and X2 are placed in the equation y=w1X1+w2X2+B and predict Y , what are we predicting here ? we do not have Y values apart from 0 and 1 classes ? could you please the problem statement once more

sascharo commented 9 months ago

X1 and X2 are the x and y coordinates in a cartesian coordinate system, respectively, and y is the label/class we're trying to predict. The decision boundary simply separates the two classes we have. We need only 0 and 1; there are only two classes.

output

kumarsiddappa-git commented 9 months ago

Thanks