<p>The accuracy of forecasts generated by each modelling framework was measured by mean AUC and reported for each major taxonomic group. Error bars represent ±1 standard error of the mean. The dashed line indicates the rule-of-thumb for good predictions (AUC = 0.8). Abbreviations: ANN = artificial neural networks, CTA = classification tree analysis, GAM = generalised additive models, GBM = generalised boosted models, GLM = generalised linear models, MARS = Multivariate adaptive regression splines, MaxEnt = maximum entropy models, Mn(PA) = prediction mean from all presence-absence modelling frameworks, RF = random forests, SRE = surface range envelopes.</p
<p>The mean, absolute difference between observed titers for viruses isolated in a given year and ti...
<p>Mean squared error (MSE) in predictions is presented for each model at each forecast horizon (1, ...
A: α = 0.3; β = ±log(1.5). B: α = 0.3; β = ±log(1.75). C: α = 0.5; β = ±log(1.5). D: α = 0.5; β = ±l...
<p>Mean sensitivity and specificity of forecasts generated by each modelling framework for (A) butte...
Average accuracy, recall, precision, MCC, and AUC measures over 10 folds for the three effector pred...
Crop models are important tools for impact assessment of climate change, as well as for exploring ma...
<p>MSE<sub>mean</sub>: mean squared error averaged over 100 models; AUC<sub>mean</sub>: area under t...
The values shown are the same scores as in Fig 3, for forecasting horizons up to three weeks. The p-...
[[sponsorship]]統計科學研究所[[note]]已出版;[SCI];有審查制度;不具代表性[[note]]http://gateway.isiknowledge.com/gateway/G...
<p>Each value is averaged over 100 independent runs with random divisions of training set and probe...
<p>Prediction accuracy was measured for each species by AUC, sensitivity, and specificity of the ent...
<p>Average area under the curve of the receiver operator characteristic (AUC) for each species (mean...
Ensemble forecasting is, so far, the most successful approach to produce relevant forecasts with an ...
ROC AUC values are averaged across 200 80–20 data splits. Error bars indicate the standard error acr...
The article presents assessment of the model accuracy estimation methods participating in CASP11. Th...
<p>The mean, absolute difference between observed titers for viruses isolated in a given year and ti...
<p>Mean squared error (MSE) in predictions is presented for each model at each forecast horizon (1, ...
A: α = 0.3; β = ±log(1.5). B: α = 0.3; β = ±log(1.75). C: α = 0.5; β = ±log(1.5). D: α = 0.5; β = ±l...
<p>Mean sensitivity and specificity of forecasts generated by each modelling framework for (A) butte...
Average accuracy, recall, precision, MCC, and AUC measures over 10 folds for the three effector pred...
Crop models are important tools for impact assessment of climate change, as well as for exploring ma...
<p>MSE<sub>mean</sub>: mean squared error averaged over 100 models; AUC<sub>mean</sub>: area under t...
The values shown are the same scores as in Fig 3, for forecasting horizons up to three weeks. The p-...
[[sponsorship]]統計科學研究所[[note]]已出版;[SCI];有審查制度;不具代表性[[note]]http://gateway.isiknowledge.com/gateway/G...
<p>Each value is averaged over 100 independent runs with random divisions of training set and probe...
<p>Prediction accuracy was measured for each species by AUC, sensitivity, and specificity of the ent...
<p>Average area under the curve of the receiver operator characteristic (AUC) for each species (mean...
Ensemble forecasting is, so far, the most successful approach to produce relevant forecasts with an ...
ROC AUC values are averaged across 200 80–20 data splits. Error bars indicate the standard error acr...
The article presents assessment of the model accuracy estimation methods participating in CASP11. Th...
<p>The mean, absolute difference between observed titers for viruses isolated in a given year and ti...
<p>Mean squared error (MSE) in predictions is presented for each model at each forecast horizon (1, ...
A: α = 0.3; β = ±log(1.5). B: α = 0.3; β = ±log(1.75). C: α = 0.5; β = ±log(1.5). D: α = 0.5; β = ±l...