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2012 | OriginalPaper | Buchkapitel

Selecting an Appropriate Interestingness Measure to Evaluate the Correlation between Syndrome Elements and Symptoms

verfasst von : Lei Zhang, Qi-ming Zhang, Yi-guo Wang, Dong-lin Yu

Erschienen in: New Frontiers in Applied Data Mining

Verlag: Springer Berlin Heidelberg

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In order to select the best interestingness measure appropriate for evaluating the correlation between syndrome elements and symptoms, 60 objective interestingness measures were selected from different subjects. Firstly, a hypothesis for a good measure was proposed. Based on the hypothesis, an experiment was designed to evaluate the measures. The experiment was based on the clinical record database of past dynasties including 51,186 clinical cases. The selected dataset in this study had 44,600 records. Han and Re were selected as the experimental syndrome elements. Three indicators calculated according to the distances between two syndrome elements were obtained in the experiment and were combined into one indicator. The

Z score, φ-coefficient

and

Kappa

were selected from 60 measures after the experiment. The

Z score

and

φ- coefficient

were selected according to subjective interestingness. Finally, the

φ- coefficient

was selected as the best measure for its low computational complexity. The method introduced in this paper may be used in other similar territories. Further research of traditional Chinese medicine can be made based on the conclusion made in this paper.

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Metadaten
Titel
Selecting an Appropriate Interestingness Measure to Evaluate the Correlation between Syndrome Elements and Symptoms
verfasst von
Lei Zhang
Qi-ming Zhang
Yi-guo Wang
Dong-lin Yu
Copyright-Jahr
2012
Verlag
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-642-28320-8_32