Straight line in roc curve

Question

This question was migrated from Stack Overflow because it can be answered on Cross Validated. Migrated 4 days ago .

Hi, what does the green straight line at the end of the plot indicate? Is there some problem with the model?

Answer 1

Possibility 1 (likely)<\/h3>

When you increase the sensitivity you can do this in small steps until (apparently) a true positive rate of about 65%. After that, the model makes a big jump to 100%. This can occur for instance when 35% of your positive cases have all the same value (eg zero).

Your model is computed for points, but you draw a line in between them.

If you want to have a positive rate in between 65% and 100% then you can do this by mixing the models with sensitivity of 65% and 100%. (See: Combining classifiers by flipping a coin<\/a> )

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Theoretically, this might also occur if the positive and negative populations have the same distribution density (with only a difference in a constant) in the region where the predictor parameter is set for high sensitivity.

However, in the special case that all the values are all the same (as in the first case), eg. zero, then you don't get statistical fluctuations.

<\/h3>

It might be that you don't compute the entire ROC curve, but the front-end that plots the curve automatically and completes the curve by connecting the end of your computed curve with the point 1,1

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Answer 2

Thank you so much for the explanation! When you say 'This can occur for instance when 35% of your positive cases have all the same value (eg zero).'<\/em> you don't mean negative cases? because if the value is 0 its mean that its negative cases

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