Sentence examples for methodologies for avoiding from inspiring English sources

Based on this, only typical methodologies for avoiding over-fitting occurrences and maintaining high generalization ability were considered in this work (e.g. selecting appropriate training algorithms for the employed ML models, as outlined in the sequel; setting not too strict termination criteria during training; etc).

The benefit of such populations is that they allow the use of linkage and association genetic methodologies for genetic analysis, while avoiding the difficulties imposed by highly structured association mapping populations (Mackay and Powell 2007).

Other solutions for single-stage methodology avoid the need for inversion are under development e.g. [Legarra A, Ducrocq V: Computational strategies for national integration of phenotypic, genomic and pedigree data in a single-step BLUP, submitted].

This review highlights the need for an improved methodology to avoid the distortional diffusional effects in the determination of CaO deactivation curves.

As Etests deliver a controlled concentration gradient of antibiotic into the agar, errors in the preparation of the media and antibiotic dilutions required for synergy testing using checkerboard and time kill methodology are avoided.

The paper argues that, despite its process orientation, design methodology cannot avoid addressing questions concerning the nature of the products being designed for two reasons.

Our methodology specifically avoids this.

Harrower [ 15] puts forth a methodology that avoids classification altogether by placing the highest and lowest values at each end of a continuous colour ramp and placing the remaining data proportionally along that continuum for each map frame.

The GLM methodology avoids potential biases resulting from the Duan smearing method for retransforming the predicted coefficient from log-transformed cost data [ 30, 32].

Stepwise methodology avoids collinearity between variables.

This methodology can help avoid some of the potential biases inherent in standard, retrospective meta-analyses.