This study proposed four approaches combining with the KNN (K-nearest neighbor) classifier for features selection that retains sufficient information for ...

The results suggest that hybrid credit scoring models are robust and effective in finding optimal subsets and the compound procedure is a promising method ...

This study proposed four approaches combining with the KNN (K-Nearest Neighbor) classifier for features selection that retains sufficient information for ...

This study proposed four approaches combining with the KNN (K-Nearest Neighbor) classifier for features selection that retains sufficient information for ...

This study proposed four approaches combining with the KNN (K-Nearest Neighbor) classifier for features selection that retains sufficient information for ...

This study proposed four approaches combining with the KNN (K-Nearest Neighbor) classifier for features selection that retains sufficient information for ...

Bibliographic details on The Hybrid Credit Scoring Strategies Based on KNN Classifier.

We propose a new feature selection strategy based on rough sets and particle swarm optimization (PSO). Rough sets have been used as a feature selection ...

In this paper, the authors propose four approaches that combine four well-known classifiers, such as K-Nearest Neighbor (KNN), Support Vector Machine (SVM), ...

In this paper, the aim is to improve predictive performance by presenting a new hybrid ensemble credit scoring model through the combination of two data pre- ...