Exact(39)
The training and testing of our models was performed using the Weka machine learning suite [35].
Matching for the 3D models was performed using a linear time normalization technique.
The optimization of the spreadsheets of these DEA models was performed using the standard, built-in Excel Solver function.
The calibration of models was performed using the nonlinear least squares optimization methods, by programming in Mathematica and by applying the genetic Algorithm, and using the traditional linear least squares method.
A comparison of these models was performed using the magnitude of the coefficient of determination R2 for the linear models and the value of the sum of normalised errors (SNE) for linear and non-linear models.
The mapping of the 3D gene expression data and the GFP fate maps to the reference models was performed using the Amira 4.1 software from Mercury Computer Systems.
Similar(21)
All models were performed using STATA v13.0.
Comparisons across models were performed using cross-validation techniques.
All multilevel models were performed using MLwiN V.2.25.
In addition, MLR and BNT models were performed using MATLAB, and SVM model was performed using LibSVM developed by Chang and Lin [ 56].
The GLM and Q models were performed using a general linear model program.
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