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The part returns a dataset which contains the original samples. In addition it returns many synthetic minority samples, depending upon the proportion that you choose to specify.

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Some scientists have investigated whether SMOTE is powerful on superior-dimensional or sparse details, such as knowledge Utilized in textual content classification or genomics datasets.

The explanation is always that SMOTE is meant for strengthening a model for the duration of teaching, not for scoring. You may perhaps get an error if a published predictive pipeline includes the SMOTE component.

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