<p>This figure illustrates the effectiveness of the weighted regularization (prior knowledge) at simulation time interval using dataset (ii). The histogram represents the number of true positive (TP), false positive (FP), and false negative (FN) findings for each as red, blue, and green bars, respectively. Black lines with circles and crosses represent ‘precision rate (PR)’ and ‘recall rate (RR)’, respectively. The values of the histogram and lines correspond to the left and right axes, respectively.</p
In all graphs, the collective strength G of the Go weights is depicted in green, while the negative ...
BR—Bayesian Regularization training, LM -Levenberg-Marquardt training algorithm, SCG—Scaled Conjugat...
<p>Time in hours to fit the algorithm (left column) and scaled pAUC for false positive rates up to 1...
(a) Top row: the raw spike-triggered average computed using different amounts of data (from left to ...
<p>(<b>A-C</b>) Model-selection accuracy was inferentially compared between the three techniques on ...
<p>Bar chart compares mean prediction correlation of FIR STRFs estimated using alternative regulariz...
The analytical noise ceiling estimator for the correlation coefficient in blue and its [5 95] percen...
<p>(a) Time course of prediction accuracy. Solid lines indicate prediction accuracy for V1 (red) and...
<p>A) A two-dimensional example illustrate how a two-class classification between the two data sets ...
A: Encoding models used in simulation 1. B: Steps taken in each repetition of simulation 1. See main...
<p>Simulation with 100 unknown QTL, 500 markers and 250 individuals in each training and testing set...
This paper is a selective review of the regularization methods scattered in statistics literature. W...
<p>Percent bias using (A) SV and (B) REP transformations and relative error using (C) SV and (D) REP...
Within each growth layout, a logistic regression was performed to classify connection existence from...
<p>We show the prediction accuracy (that is, the fraction of correct rating predictions) as a functi...
In all graphs, the collective strength G of the Go weights is depicted in green, while the negative ...
BR—Bayesian Regularization training, LM -Levenberg-Marquardt training algorithm, SCG—Scaled Conjugat...
<p>Time in hours to fit the algorithm (left column) and scaled pAUC for false positive rates up to 1...
(a) Top row: the raw spike-triggered average computed using different amounts of data (from left to ...
<p>(<b>A-C</b>) Model-selection accuracy was inferentially compared between the three techniques on ...
<p>Bar chart compares mean prediction correlation of FIR STRFs estimated using alternative regulariz...
The analytical noise ceiling estimator for the correlation coefficient in blue and its [5 95] percen...
<p>(a) Time course of prediction accuracy. Solid lines indicate prediction accuracy for V1 (red) and...
<p>A) A two-dimensional example illustrate how a two-class classification between the two data sets ...
A: Encoding models used in simulation 1. B: Steps taken in each repetition of simulation 1. See main...
<p>Simulation with 100 unknown QTL, 500 markers and 250 individuals in each training and testing set...
This paper is a selective review of the regularization methods scattered in statistics literature. W...
<p>Percent bias using (A) SV and (B) REP transformations and relative error using (C) SV and (D) REP...
Within each growth layout, a logistic regression was performed to classify connection existence from...
<p>We show the prediction accuracy (that is, the fraction of correct rating predictions) as a functi...
In all graphs, the collective strength G of the Go weights is depicted in green, while the negative ...
BR—Bayesian Regularization training, LM -Levenberg-Marquardt training algorithm, SCG—Scaled Conjugat...
<p>Time in hours to fit the algorithm (left column) and scaled pAUC for false positive rates up to 1...