[HN Gopher] Decision Trees in Python: Predicting Diabetes - Stat...
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       Decision Trees in Python: Predicting Diabetes - Statistically
       Relevant
        
       Author : rbanffy
       Score  : 26 points
       Date   : 2022-10-06 21:03 UTC (1 hours ago)
        
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       | teruakohatu wrote:
       | Two things are missing here.
       | 
       | The first the the null model result, if a model simply predicted
       | the most common class, we would get accuracy of 0.649. So the
       | CART model has increased performance by ~14%. A good start.
       | 
       | The second is that in many scenarios in business and especially
       | medical scenarios, you also need to know sensitivity (how good
       | are we at predicting a person with diabetes does have diabetes)
       | and specificity (how good are we at predicting a person without
       | diabetes does NOT have it). Always calculate these metrics and a
       | confusion matrix for binary classification.
       | 
       | If a simple model predicted you had low vitamin-C, a doctor in my
       | country would simply prescribe it even if the model had terrible
       | specificity because the treatment is harmless and cheaper than a
       | blood test. On the other hand if a simple model predicted cancer,
       | they would refer you a variety of scans and tests and not make a
       | diagnosis until they were quite sure.
        
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       (page generated 2022-10-06 23:00 UTC)