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Results from AUC analyses, however, often contradicted results of the linear regression method used to evaluate model performance.
The survey and regression method used in this study can be adapted for finding relevant factors and suggesting appropriate compensation for other environmental and infrastructure development projects.
We report and discuss results of experiments conducted on three different datasets in infrared spectroscopy and designed in such a way to test the proposed approach by: 1) varying the kind of adopted regression method used to approximate the chemical parameter of interest.
The type of regression method used in both the previously described phases of the proposed approach was decision-tree building algorithms.
PLS is a regression method used in order to find the relationshipbetween two data tables referred to as X and Y. PLS regression [72] analysis consists in calculating by means of successive iterations, linearcombinations of the measured X-variables (predictor variables).
When validated by two highly reliable mouse transcript databases, this MMES based empirical method is shown to be remarkably more accurate than read-counting method, and also better than the logistic regression method used in Pan et al [3].
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From our results this method is better than the simple regression method using the wind speed profile, which has been widely used.
Non-linear curve-fitting regression method using parametric equation as 'user model' has been utilized to determine reactivity ratios signifying effects of terminal and penultimate groups in copolymerization.
RESULTS: In this paper, we describe a pathway-based classification and regression method using Random Forests to analyze gene expression data.
The simple linear regression method uses one variable and test the response of another variable to it.
The averages of the experimental data were fit by a nonlinear regression method using the program Igor Pro (WaveMetrics, USA).
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