Alexey Zabashta
ABSTRACT
In this paper, we propose a method for synthesis of datasets with specific characteristics for the clustering task. Namely, we propose an algorithm, which can generate a clustering dataset given its meta-feature description. The method we propose is based on an evolutionary algorithm with crossover and mutation operators that are capable to improve candidate datasets in a natural way. We experimentally compared this method with two other approaches for dataset synthesis. We used meta-feature vectors of 247 real-world datasets as inputs. The proposed method outperformed existing ones with respect to Mahalanobis distance between target meta-feature vectors and characteristics of generated datasets.
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Index Terms
- Synthesis of Datasets with Specific Characteristics for the Clustering Problem
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