<p>The black dots indicate actual simulation data set. The solid curve denotes SVR regress line and the dot line represents the MLR regression line. The simulation data set is randomly generated by MATLAB.</p
Bland—Atman plot of the SVR model with the polynomial function and the n-CCA model on the dataset wi...
Comparison of actual value of validation sample with SVR regression value of stochastic optimization...
A graph of model performance scores (precision, recall and F1) based on varying MLP depths.</p
<p>In the Data column, S1 indicates data from the first simulation method, S2 indicates data from th...
<p>Learning curves (blue line) generated for dataset using mean error rates (black squares) calcula...
Statistics of predicted bandgaps by SVR, GBDT, RF and MLP algorithms based on a 9-dimensional featur...
The plot shows the predictive performances for the different methods when normalized data were class...
<p>The simulated datasets were used to check the precision and accuracy of the ML procedure.</p><p>*...
(a) Pre-defined ROIs of the simulated data. (b) The group voxel pattern relevant to each task of PLS...
<p>A) Spatio-temporal decoding: Multivariate support vector regression (SVR) was used to regress <i>...
The SMR-predictor is visualized as in [17] with the addition of the user categories. One dot per sub...
Abstract − Instead of minimizing the observed training error, Support Vector Regression (SVR) attemp...
<p>ROC curves showing true-positive rates (sensitivity) plotted against the false-positive rate for ...
Within each growth layout, a logistic regression was performed to classify connection existence from...
<p>(For MLPD, all the available data are used. For SLPD, only the MRI features are used. The best va...
Bland—Atman plot of the SVR model with the polynomial function and the n-CCA model on the dataset wi...
Comparison of actual value of validation sample with SVR regression value of stochastic optimization...
A graph of model performance scores (precision, recall and F1) based on varying MLP depths.</p
<p>In the Data column, S1 indicates data from the first simulation method, S2 indicates data from th...
<p>Learning curves (blue line) generated for dataset using mean error rates (black squares) calcula...
Statistics of predicted bandgaps by SVR, GBDT, RF and MLP algorithms based on a 9-dimensional featur...
The plot shows the predictive performances for the different methods when normalized data were class...
<p>The simulated datasets were used to check the precision and accuracy of the ML procedure.</p><p>*...
(a) Pre-defined ROIs of the simulated data. (b) The group voxel pattern relevant to each task of PLS...
<p>A) Spatio-temporal decoding: Multivariate support vector regression (SVR) was used to regress <i>...
The SMR-predictor is visualized as in [17] with the addition of the user categories. One dot per sub...
Abstract − Instead of minimizing the observed training error, Support Vector Regression (SVR) attemp...
<p>ROC curves showing true-positive rates (sensitivity) plotted against the false-positive rate for ...
Within each growth layout, a logistic regression was performed to classify connection existence from...
<p>(For MLPD, all the available data are used. For SLPD, only the MRI features are used. The best va...
Bland—Atman plot of the SVR model with the polynomial function and the n-CCA model on the dataset wi...
Comparison of actual value of validation sample with SVR regression value of stochastic optimization...
A graph of model performance scores (precision, recall and F1) based on varying MLP depths.</p
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