Several frequently used techniques for designing classifiers of microarray data, such as support vector machine, neural networks, k-nearest neighbor, and logistic regression model, suffer from low interpretabilities.
Although, apart from the models accuracy, its low complexity, interpretability as well as its simple tree structure are most desirable properties for the DRG application.
Some criteria for low-level interpretability and high-level interpretability are identified, respectively.
The low-level interpretability of fuzzy models refers to fuzzy model interpretability achieved by optimizing the membership functions in terms of semantic criteria on fuzzy set level, while the high-level interpretability refers to fuzzy model interpretability obtained by dealing with the coverage, completeness, and consistency of the rules in terms of the criteria on fuzzy rule level.
Thus the MGFS model keeps interpretability, low computational cost and high generalization.
The reported experiences showed the suitability of our software for selecting sets of descriptors with low cardinality, high interpretability, low redundancy and high statistical performance in a visual exploratory way.
However, individual gene-based signatures usually suffer from low reproducibility and interpretability.
Although respondents of the pilot study did not make remarks with respect to interpretation, open interpretability is relevant to all questions possibly most to those with a low score.
Here, a special form of the Korf-function developed by Lappi (1997) is used, which is distinguished by the biological interpretability and comparatively low correlation of its parameters.
As a result, the factorial genetic analyses had very low statistical power, substantially limiting the interpretability of those findings.
