<p>Bars indicate the explanatory power (in terms of gain) when only a single predictor is included in the model with 95% confidence intervals.</p
Contains fulltext : 130562.pdf (publisher's version ) (Closed access
Feature importance (odds coefficients) bar chart for final logistic regression model.</p
Variable importance measured as the scaled mean decrease in accuracy of each variable in the Baselin...
Blue bar = Shows importance of each variables in explaining the variation in the data when used sepa...
Jackknife test showing the importance of each variable independently, when building the Maxent model...
<p>Overall relative importance of predictor variables for invasive species from Jackknife test.</p
<p>The plot shows how environmental variables can increase or reduce the gain when solely used or om...
<p>The figures show each variable’s contribution to (A) regularized training gain, and (B) test AUC ...
<p>Each curve represents the regularized training gain of each variable used in isolation for each s...
<p>Jacknife analysis for <i>Montipora</i>, <i>Leptoseris</i> and <i>Porites</i> showing the mean AUC...
<p>Results of jackknife test of relative importance of predictor variables for Chinese caterpillar f...
<p>Results of Maxent model showing jackknife tests of variable importance for training samples.</p
<p>Jackknife tests (%) and the mean feature numbers of the SVM-based predictors for 30 samples.</p
<p>For each species, the table shows the area under the curve (AUC) and regularized training gain (G...
<p>Selected model coefficients, confidence interval and relative importance of the variables used.</...
Contains fulltext : 130562.pdf (publisher's version ) (Closed access
Feature importance (odds coefficients) bar chart for final logistic regression model.</p
Variable importance measured as the scaled mean decrease in accuracy of each variable in the Baselin...
Blue bar = Shows importance of each variables in explaining the variation in the data when used sepa...
Jackknife test showing the importance of each variable independently, when building the Maxent model...
<p>Overall relative importance of predictor variables for invasive species from Jackknife test.</p
<p>The plot shows how environmental variables can increase or reduce the gain when solely used or om...
<p>The figures show each variable’s contribution to (A) regularized training gain, and (B) test AUC ...
<p>Each curve represents the regularized training gain of each variable used in isolation for each s...
<p>Jacknife analysis for <i>Montipora</i>, <i>Leptoseris</i> and <i>Porites</i> showing the mean AUC...
<p>Results of jackknife test of relative importance of predictor variables for Chinese caterpillar f...
<p>Results of Maxent model showing jackknife tests of variable importance for training samples.</p
<p>Jackknife tests (%) and the mean feature numbers of the SVM-based predictors for 30 samples.</p
<p>For each species, the table shows the area under the curve (AUC) and regularized training gain (G...
<p>Selected model coefficients, confidence interval and relative importance of the variables used.</...
Contains fulltext : 130562.pdf (publisher's version ) (Closed access
Feature importance (odds coefficients) bar chart for final logistic regression model.</p
Variable importance measured as the scaled mean decrease in accuracy of each variable in the Baselin...
DOI
Add to ORKG