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Elimination of cross-correlation effect on result of clusterization

Elimination of cross-correlation effect on result of clusterization. Kyryl Iurchenko , PhD student. Taras Shevchenko Kyiv National University, Faculty of Economics, Department of Economic Cybernetics, Kyiv. Problem:

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Elimination of cross-correlation effect on result of clusterization

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  1. Elimination of cross-correlation effect on result of clusterization KyrylIurchenko, PhD student. Taras Shevchenko Kyiv National University, Faculty of Economics, Department of Economic Cybernetics, Kyiv • Problem: • Increasing volume of data about analyzed objects and its sources leads to necessity of using more sophisticated algorithms. • At the same time increasing of number of each object characteristics affects number of correlated features. • It can bias results and increase weight of more correlated features. • Proposed solution: • Forecasts of each characteristics based on other features will be used as input into clusterization algorithm for incorporation of cross-correlation between characteristics. • Result: • It gives better possibility to take into consideration nonlinearity in analyzed data.

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