Sentence examples for partitioning of the variable from inspiring English sources

As described in [ 13], fuzzy set is a common tool for facilitating the interpretation of rules in linguistic terms, and avoiding unnatural boundaries in the partitioning of the variable domains.

Finally, measuring robustness for different partitions of the variables (all 13 characteristics; 5 essentials; 8 common) lets us reach conclusions about which of these partitions may be more meaningful and in that sense better.

In this paper, we propose a new method to perform sensitivity analysis through a partitioning of the input variables into these two groupings: regressive variables and model parameters.

The hierarchical partitioning of the independent variables was computed with the package hier.part (Walsh and Mac Nally 2013).

The model complexity is minimized in a structure selection search, performed by a genetic algorithm that selects simultaneously the most representative subset of variables and also the number of fuzzy sets in the fuzzy partition of the selected variables.

In order to make good use of the structural information in rule base to decrease the conservatism of the stability analysis, the standard fuzzy partition of the input variables of fuzzy control systems is well defined.

Differently from the existing approaches, the proposed method provides full order mode-dependent controllers constructed in terms of the state space matrices of the operation modes and partitions of the slack variables introduced in the design conditions.

Recent research has raised the possibility that fetal lead exposure is not estimated adequately by measuring lead content in maternal whole blood lead because of the variable partitioning of lead in whole blood between plasma and red blood cells.

The sub-group with perceived need was further partitioned using the variable 'knowledge of correct use' and condom use was 94% for people with knowledge and 67% for people without knowledge.

Successive p-variable partitioning of the n-dimensional design space (with p⪯¡n) are applied to adapt the simplex optimization to large dimensions.

It builds a decision tree from the training data using recursive partitioning of the space representing the predictive variables and based on the information gain ratio.