For best performance, use the most appropriate feature class when displaying or printing.
Three top-down and one bottom-up approaches are evaluated for retrieving the most appropriate feature sets in terms of highest classification rates.
This is the same future climate model utilized by Rodda et al. [2] We applied the default regularization parameter (1.0), and allowed the algorithm to choose the most appropriate "feature" type based on sample size by utilizing the auto-feature option [6].
Here, the most appropriate classifier, features, discretization algorithm, adjustment method for missing data, and derivation dataset are selected in order to develop the highest performing predictive models.
This step aims to develop the highest performing models through the selection of the most appropriate classifier, features, discretization algorithm, adjustment method for missing data, and derivation dataset.
The Naive Bayes classification approach revealed the importance of feature selection and allowed us to determine the most appropriate combination of features for optimal enhancer identification, however, each feature is assumed to contribute independently.
Should the most appropriate tool lack features needed to fully implement the strategy, such as log parsing which is underrepresented in the feature lists of many monitoring tools, additional tools can be incorporated into the implementation of the strategy.
Since the nature of the Vietnamese language is different from English, we used the most appropriate and reasonable features to achieve optimum accuracy for the system.
For effective case retrieval, a Genetic Algorithm mechanism is employed to determine the most appropriate two-level feature weights.
