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A logistical model was then built by utilizing the forward selection method based on the nine genes from the previous step using the SAS PROC LOGISTIC procedure [ 8].
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We thus utilize the forward-selection procedure, described above, to determine which of the first three axes of genetic variation are correlated with phenotype.
COI sequences were obtained utilizing the forward primer LCO1490 [ 37], and the reverse primers HCO2198 [ 37] or COX-B7R [ 38].
Retention factors were used as the target property to build two QSRR models utilizing the conventional forward selection and the advanced nature-inspired firefly algorithm for descriptor selection, coupled with multiple linear regression.
The forward selection fitting algorithm can be improved as well.
Since both backward and forward model selection methods produced similar results, data from the forward selection model are presented.
Binomial regression models predicting depression utilized forward selection model building with total concussion history as the main exposure.
Genotype selection was then performed using the forward-selection and backward-elimination scheme.
The sequential forward selection, genetic and maximum relevance minimum redundancy algorithms are used for a precise selection of features.
For selection, the fast forward selection algorithm, least angle regression (LARS), is used, but it is not robust.
LARS is similar to the traditional forward selection method.
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