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1. Managing imbalanced training data by sequential segmentation in machine learning
Master-uppsats, Linköpings universitet/Avdelningen för medicinsk teknikSammanfattning : Imbalanced training data is a common problem in machine learning applications. Thisproblem refers to datasets in which the foreground pixels are significantly fewer thanthe background pixels. By training a machine learning model with imbalanced data, theresult is typically a model that classifies all pixels as the background class. LÄS MER
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