<p>Each row represents the actual variety and in which one was classified. Bolded values (diagonal of the matrix) are the number of samples properly classified. The last column shows the correctly classified percentage for each variety.</p><p>ANN: Artificial Neural Network; SNV+D: Standard Normal Variate followed by De-trending; D2W5: Second-degree derivative and window size 5 Savitzky-Golay filter.</p><p>Ve: Verdejo; M: Malvasia; V: Viura; A: Albariño; T: Treixadura; G: Godello; WG: White Grenache; WT: White Tempranillo; PX: Pedro Ximénez; Vi: Viognier; CF: Cabernet Franc; Gr: Grenache; CS: Cabernet Sauvignon; C: Carmenere; S: Syrah; Te: Tempranillo; PN: Pinot Noir; Ca: Caladoc; Ma: Marselan; TN: Touriga Nacional.</p><p>Confusion matrix fr...
The area of each square represents the value of each matrix entry. Values are counts averaged across...
Classifications of the validation data (columns) are compared to the ground truth (rows). Numbers ar...
The colours of the heat map correspond to the percentage of classification in each category. The acc...
<p>Each row represents the actual variety and in which one was classified. Bolded values (diagonal o...
<p>The upper number in each entry of the matrix is the average number of actual recognised classes i...
The correctly classified data is reflected along the diagonal regions. The misclassified is reflecte...
<p>The rows hereby indicate the predicted, i.e. real class, whereas the columns indicate the actual ...
Confusion matrix for the best classification model, which corresponded to a neural network with four...
<p>Panel A: Confusion matrices for identifying one of the four tasks from one day to another for eac...
<p>The rows represent the true pollen types while the columns indicate how the images have been clas...
<p><b>A.</b> Classification result over all 21 neurons. Blue stars and red circle denote the classif...
The confusion matrix representing the computed classification accuracy % for the proposed research w...
<p>These are NB (A) and SVM-R (B). The color code indicates average accuracy per composition (the hi...
Confusion matrix showing the results of the testing phase for the AlexNet neural network.</p
<p>Rows indicate the percentages of predicted syndromes for each of the syndromes in the study.</p><...
The area of each square represents the value of each matrix entry. Values are counts averaged across...
Classifications of the validation data (columns) are compared to the ground truth (rows). Numbers ar...
The colours of the heat map correspond to the percentage of classification in each category. The acc...
<p>Each row represents the actual variety and in which one was classified. Bolded values (diagonal o...
<p>The upper number in each entry of the matrix is the average number of actual recognised classes i...
The correctly classified data is reflected along the diagonal regions. The misclassified is reflecte...
<p>The rows hereby indicate the predicted, i.e. real class, whereas the columns indicate the actual ...
Confusion matrix for the best classification model, which corresponded to a neural network with four...
<p>Panel A: Confusion matrices for identifying one of the four tasks from one day to another for eac...
<p>The rows represent the true pollen types while the columns indicate how the images have been clas...
<p><b>A.</b> Classification result over all 21 neurons. Blue stars and red circle denote the classif...
The confusion matrix representing the computed classification accuracy % for the proposed research w...
<p>These are NB (A) and SVM-R (B). The color code indicates average accuracy per composition (the hi...
Confusion matrix showing the results of the testing phase for the AlexNet neural network.</p
<p>Rows indicate the percentages of predicted syndromes for each of the syndromes in the study.</p><...
The area of each square represents the value of each matrix entry. Values are counts averaged across...
Classifications of the validation data (columns) are compared to the ground truth (rows). Numbers ar...
The colours of the heat map correspond to the percentage of classification in each category. The acc...