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I'm working on a multi-class classification problem and want to make predictions with high precision for a single class only (i.e. to predict less but correctly).

I've high lighted the total number of predictions and True positive cases for class-1. Any suggestion, how to tune the model of high precision?

PS: Result of other classes don't matter, we are only focusing on the precision of class-1. Please find the results below

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Tejas Pandya
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Kamal Sidhu
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One of the possible issues over here can be the class imbalance problem. Due to the unequal size of samples in your dataset, the model you have developed might be biased to a particular class. Keeping a similar sample size for all the classes may increase your precision/accuracy. Hope this helps

Dhaval Thakkar
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  • I've already oversampled the training dataset (using SMOTE) as you can see training dataset is equally distributed among all classes. – Kamal Sidhu Mar 13 '19 at 04:45