Improving a model
Lesson 4 / 6
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I can make changes to how my model is trained to improve the accuracy of the output.
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Data cleaning can remove outliers so the model "learns" real patterns instead of noise.
False positives occur when data is misclassified.
Creating a null class reduces the chances of misclassification.
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