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Genetic algorithms [27] and principle component analysis [18] were compared to examine their ability to select features that are useful while using various linear and nonlinear methods for classification.
Genetic algorithms [27] and principle component analysis [18] were compared for their ability to select features while using various linear and nonlinear methods for classification.
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Of course, one can always compute a linear basis for the left nullspace of a stoichiometric matrix using various linear algebraic algorithms, but then biochemical interpretation of each basis vector is problematic.
These studies were performed using various linear-based methods, including conventional linear regression methods [ 11, 12], a weighted correlation network method [ 8, 10], and a multidimensional scaling method [ 9].
The specimen was cured using various isothermal and linear heating regimes.
The statistical analyses were performed using various generalized linear models (GLM) with link functions depending on the nature of the response variables (i.e., continuous or binomial).
Therefore, benzylamine was added to form ring-opened syn-2,3-THF 32 in 70%% yield with excellent levels of diastereoselectivity (98 2 d.r. syn / anti ) and enantioselectivity (99%% ee syn).[ 19] The scope of this process was then investigated by using various substituted linear enone acids.
Kwok et al. [8] performed a comprehensive study on parameter and usage protocols for using various nonlinear and equivalent linear ground response analysis approaches.
Associations between genotype and intelligence were evaluated using various statistical tests; linear regression, logistic regression, Chi2.
In an attempt to demonstrate the non-linear nature of this system, we have printed fluorescent colour palettes (Fig. 6a−f) using various ink concentrations and different CBAs.
It has been solved using various approaches, including branch and bound linear programming, tabu search, simulated annealing, and genetic algorithms.
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