By implementing classifications with the selected features, it is demonstrated that the selected features have good discriminative power.
In the VCA method, after the Grobner basis of vanishing ideal is calculated, it is possible to implement classification via the classification decision function.
To further illustrate the potential prognostic application of pathway L values, we implemented classification models built on genes identified by a published methodology for gene expression analysis, and compared the resulting prediction performances against the results reported above.
Based on a comparison of four classification systems, Müller-Staub [ 8] concluded that the NANDA-I classification is the best-researched and internationally most widely implemented classification system.
In contrast, the "white-box" models, such as Decision Trees [ 4], Rough Sets [ 5], and emerging patterns (EPs) [ 6], often implement classification by giving "IF-THEN -like rules.
To further assess the potential predictive relevance of our approach, we implemented classification models based on network neighbourhoods retrieved by the STRING system [ 23].
Among the properties, we selected features which show different tendencies between the two groups and implemented classifications using support vector machine, random forest, and linear logistic regression methods to confirm whether or not these features can identify LoF and GoF mutations.
MATLAB packages are used for implementing SVM classification.
For example, having an initial destination and source as input, the app should select the optimal route and help to find proper locations on the way, which has been done by implementing a classification model.
