The paper proposes combining simple random sampling with k-fold cross-validation via a weighted factor and claims improved partition accuracy on synthetic normal data.
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Fusion Sampling Validation in Data Partitioning for Machine Learning
The paper proposes combining simple random sampling with k-fold cross-validation via a weighted factor and claims improved partition accuracy on synthetic normal data.