<p>Here, TP (true positive) and TN (true negative) denote the number of correctly predicted overlap residues and the correctly predicted non-overlap residues respectively. FP (false positive) and FN (false negative) refer to wrong predictions of overlap and non-overlap residues.</p
<p>Matrix delineates distribution of actual compared with predicted class membership for multiclass ...
<p>Confusion matrix—observed and predicted values obtained using the Cavnar and Trenkle procedure fo...
<p>All <i>in silico</i> experiments were evaluated with 10-fold cross-validation. TP means an instan...
<p>TP: true positives, FP: false positives, FN: false negatives, TN: ...
<p><i>TP</i> is the number of correct predictions that an instance is positive (<i>true positive</i>...
<p>TP = true positive; FP = false positive; FN = false negative; TN = true negative.</p
<p>(A) The left oval shows two actual labels: positives (P; blue; top half) and negatives (N; red; b...
<p>The definitions of true and false positives (resp. TP and FP), true and false negatives (resp. TN...
++<p>, <sup>−+</sup>, <sup>−−</sup>, <sup>+−</sup> denote true positive, false positive, false negat...
Confusion matrices reports TP, FN on the first row and FP, TN on the second row. Sensitivity calcula...
The top-left represents the TN, the top-right represents FP, the bottom-left is FN and the bottom-ri...
Confusion matrices reports TP, FN on the first row and FP, TN on the second row. Sensitivity calcula...
A 14 × 14 confusion matrix: Prediction based on the MLR-HomoNet method for the testing data .</p
A 14 × 14 confusion matrix: Prediction based on the LR-HeteNet method for the testing data .</p
<p>Representative result of confusion matrix between true labels and predicted labels by DCNN withou...
<p>Matrix delineates distribution of actual compared with predicted class membership for multiclass ...
<p>Confusion matrix—observed and predicted values obtained using the Cavnar and Trenkle procedure fo...
<p>All <i>in silico</i> experiments were evaluated with 10-fold cross-validation. TP means an instan...
<p>TP: true positives, FP: false positives, FN: false negatives, TN: ...
<p><i>TP</i> is the number of correct predictions that an instance is positive (<i>true positive</i>...
<p>TP = true positive; FP = false positive; FN = false negative; TN = true negative.</p
<p>(A) The left oval shows two actual labels: positives (P; blue; top half) and negatives (N; red; b...
<p>The definitions of true and false positives (resp. TP and FP), true and false negatives (resp. TN...
++<p>, <sup>−+</sup>, <sup>−−</sup>, <sup>+−</sup> denote true positive, false positive, false negat...
Confusion matrices reports TP, FN on the first row and FP, TN on the second row. Sensitivity calcula...
The top-left represents the TN, the top-right represents FP, the bottom-left is FN and the bottom-ri...
Confusion matrices reports TP, FN on the first row and FP, TN on the second row. Sensitivity calcula...
A 14 × 14 confusion matrix: Prediction based on the MLR-HomoNet method for the testing data .</p
A 14 × 14 confusion matrix: Prediction based on the LR-HeteNet method for the testing data .</p
<p>Representative result of confusion matrix between true labels and predicted labels by DCNN withou...
<p>Matrix delineates distribution of actual compared with predicted class membership for multiclass ...
<p>Confusion matrix—observed and predicted values obtained using the Cavnar and Trenkle procedure fo...
<p>All <i>in silico</i> experiments were evaluated with 10-fold cross-validation. TP means an instan...
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