Publication date
January 2024
DOIAbstract
(a) RF, (b) GBM, (c) AdaBoost, (d) LR, (e) SVC, (f) SVEC-H, (g) SVEC-S, (h) CNN, (i) LSTM, (j) CNN-LSTM, and (k) SSC.</p
(a) RF, (b) GBM, (c) AdaBoost, (d) LR, (e) SVC, (f) SVEC-H, (g) SVEC-S, (h) CNN, (i) LSTM, (j) CNN-LSTM, and (k) SSC.</p
The confusion matrix representing the computed classification accuracy % for the proposed research w...
The confusion matrix representing the computed classification accuracy % for the proposed research w...
<p>Confusion matrix of a classifier based on the gold standard of class labels.</p
(a) RF, (b) GBM, (c) AdaBoost, (d) LR, (e) SVC, (f) SVEC-H, (g) SVEC-S, (h) CNN, (i) LSTM, (j) CNN-L...
<p>Confusion matrix for the classifiers of RF, SVM, and WKNN using the input dataset with all the pr...
(1) only each prediction model after data preprocessing, where (a) LR, (c) RF, (e) GB, (g) DNN, (i) ...
The correctly classified data is reflected along the diagonal regions. The misclassified is reflecte...
<p>These are NB (A) and SVM-R (B). The color code indicates average accuracy per composition (the hi...
Since each classifier distinguishes between the desired class and every “other” class, the confusion...
<p>(UA, user’s accuracy; PA, producer’s accuracy; OA, overall accuracy; Kappa, Kappa statistics; UNC...
<p>The rows hereby indicate the predicted, i.e. real class, whereas the columns indicate the actual ...
<p>The classification precision and recall values are shown for each class in all the tables. The ce...
Confusion matrix (error matrix): the entry in row k and column l is the number of test datapoints wh...
<p>Confusion matrix for classification by the statistical models versus the empirical models.</p
<p>Confusion matrix of the result of the support vector machine classifier for the diagnosis.</p
The confusion matrix representing the computed classification accuracy % for the proposed research w...
The confusion matrix representing the computed classification accuracy % for the proposed research w...
<p>Confusion matrix of a classifier based on the gold standard of class labels.</p
(a) RF, (b) GBM, (c) AdaBoost, (d) LR, (e) SVC, (f) SVEC-H, (g) SVEC-S, (h) CNN, (i) LSTM, (j) CNN-L...
<p>Confusion matrix for the classifiers of RF, SVM, and WKNN using the input dataset with all the pr...
(1) only each prediction model after data preprocessing, where (a) LR, (c) RF, (e) GB, (g) DNN, (i) ...
The correctly classified data is reflected along the diagonal regions. The misclassified is reflecte...
<p>These are NB (A) and SVM-R (B). The color code indicates average accuracy per composition (the hi...
Since each classifier distinguishes between the desired class and every “other” class, the confusion...
<p>(UA, user’s accuracy; PA, producer’s accuracy; OA, overall accuracy; Kappa, Kappa statistics; UNC...
<p>The rows hereby indicate the predicted, i.e. real class, whereas the columns indicate the actual ...
<p>The classification precision and recall values are shown for each class in all the tables. The ce...
Confusion matrix (error matrix): the entry in row k and column l is the number of test datapoints wh...
<p>Confusion matrix for classification by the statistical models versus the empirical models.</p
<p>Confusion matrix of the result of the support vector machine classifier for the diagnosis.</p
The confusion matrix representing the computed classification accuracy % for the proposed research w...
The confusion matrix representing the computed classification accuracy % for the proposed research w...
<p>Confusion matrix of a classifier based on the gold standard of class labels.</p
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