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Other approaches are based on data mining methods.
Research interests: QSAR, applicability domain, data mining methods, network protocols.
It highly depends on selecting appropriate data mining methods for regression analysis.
The GUHA method, introduced in 1966 (see [2]), is one of the oldest data mining methods.
This makes traditional data mining methods prone to overfitting, especially with a small sample size.
The data mining methods [20] are not limited to data problem specific methods.
Learning algorithms and data mining methods were utilized towards this objective.
Computational data mining methods are important tools for the prioritization of disease candidate gene.
Data mining methods have been used to find patterns and models from clinical data [18, 19].
A major application of molecular encodings are structure-based machine learning and data mining methods.
These research analyses used traditional statistical methods as well as data mining methods.
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