Optimal Data Analyses 2.0
Optimal Data Analyses uses a powerfull algorithm based on Artificial Intelligence techniques that may be used for solving data analysis problems such as symbolic regression and classification.
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Optimal Data Analyses uses a powerfull algorithm based on Artificial Intelligence techniques that may be used for solving data analysis problems such as symbolic regression and classification.
The purpose of symbolic regression is to find a function (mathematical expression) that satisfies a set of fitness cases (data). The purpose of classification is to find a function that separates a set of data.
Optimal Data Analyses employes different errors for achiving the optimal solution: Mean Absolute Error, Mean Square Error, Root Mean Square Error and R-Square. The obtained results are displayed in various formats: graphical format, text format or mathematical formula in 4 programming languages (C, Pascal, Java and Visual Basic).
tags
mean square square error the purpose symbolic regression data analyses optimal data

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