<p>The rows hereby indicate the predicted, i.e. real class, whereas the columns indicate the actual class, corresponding to the CNN output. Thus, all values on the diagonal represent the correctly classified cells.</p
The confusion matrix representing the computed classification accuracy % for the proposed research w...
<p>Confusion matrix for the classifiers of RF, SVM, and WKNN using the input dataset with all the pr...
Since each classifier distinguishes between the desired class and every “other” class, the confusion...
Classifications of the validation data (columns) are compared to the ground truth (rows). Numbers ar...
Confusion matrix for the classification of the 724 real hESC images using the CNN architecture of De...
The correctly classified data is reflected along the diagonal regions. The misclassified is reflecte...
(1) only each prediction model after data preprocessing, where (a) LR, (c) RF, (e) GB, (g) DNN, (i) ...
The diagonal values indicate the ratio of correct classifications for each digit, while off-diagonal...
(a) RF, (b) GBM, (c) AdaBoost, (d) LR, (e) SVC, (f) SVEC-H, (g) SVEC-S, (h) CNN, (i) LSTM, (j) CNN-L...
(a) Confusion matrix for pre-stimulus segments and (b) on-going stimulus segments were presented. R ...
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...
Confusion matrix for the classification of the 724 real hESC images using the Fused CNN-Triplet arch...
Confusion matrix (error matrix): the entry in row k and column l is the number of test datapoints wh...
<p>Confusion matrix and overall performance of the classifier used to determine the sharpness of the...
The confusion matrix representing the computed classification accuracy % for the proposed research w...
<p>Confusion matrix for the classifiers of RF, SVM, and WKNN using the input dataset with all the pr...
Since each classifier distinguishes between the desired class and every “other” class, the confusion...
Classifications of the validation data (columns) are compared to the ground truth (rows). Numbers ar...
Confusion matrix for the classification of the 724 real hESC images using the CNN architecture of De...
The correctly classified data is reflected along the diagonal regions. The misclassified is reflecte...
(1) only each prediction model after data preprocessing, where (a) LR, (c) RF, (e) GB, (g) DNN, (i) ...
The diagonal values indicate the ratio of correct classifications for each digit, while off-diagonal...
(a) RF, (b) GBM, (c) AdaBoost, (d) LR, (e) SVC, (f) SVEC-H, (g) SVEC-S, (h) CNN, (i) LSTM, (j) CNN-L...
(a) Confusion matrix for pre-stimulus segments and (b) on-going stimulus segments were presented. R ...
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...
Confusion matrix for the classification of the 724 real hESC images using the Fused CNN-Triplet arch...
Confusion matrix (error matrix): the entry in row k and column l is the number of test datapoints wh...
<p>Confusion matrix and overall performance of the classifier used to determine the sharpness of the...
The confusion matrix representing the computed classification accuracy % for the proposed research w...
<p>Confusion matrix for the classifiers of RF, SVM, and WKNN using the input dataset with all the pr...
Since each classifier distinguishes between the desired class and every “other” class, the confusion...
DOI
Add to ORKG