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A common-sense baseline would the best score you could get on your validation dataset without actually looking at the individual samples. If you're looking at an imbalanced binary classification task, with 90% of your samples in class A and 10% B, then your baseline is 90% acc.
In that case a model that scores 92% is 100% more accurate than one that scores 91%. Don't start the comparison charts at 0!
non rule based method requires thought
Hey im a student, can you explain how its 100% more accurate?
And how the baseline is 90%? I get that 92 would be 100% more accurate than 91 with baseline 90.right? How's the baseline 90?
One way of looking at it is to answer this question: "what is the next best alternative for this?"
thanks bro 
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