confusion matrix


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confusion matrix

[kən′fyü·zhən ‚mā·triks]
(computer science)
In pattern recognition, a matrix used to represent errors in assigning classes to observed patterns in which the ij th element represents the number of samples from class i which were classified as class j.
References in periodicals archive ?
From the confusion matrix, a high percentage of DSB-AM signals were misclassified as SSB-AM and SSB-AM as DSB-AM (Fig.
Our result is presented in the confusion matrix presented in Fig.
8(b) illustrates corresponding ROC curve and confusion matrix for KNORA-E dynamic ensemble selection technique respectively.
These data were used as input to run the confusion function for each of the classification techniques in order to generate the corresponding confusion matrixes. From the confusion matrix the percentage of correct classification (PCC) and the Kappa index (Tso & Mather, 2009) were calculated.
Confusion matrix are the most important outputs, because it represents the connection between the class showed by HDI, also named as original class and the new class (predicted) computed using K-Means algorithm and new datasets: principal components (W) and factors (F).
Using the estimated regression coefficients and the observed data we created a confusion matrix to study the classification rate for our model.
As an example Table IV contains the confusion matrix of the first subject.
These counts are organized in a table known as a confusion matrix. In this research each classification is considered as a two-class case with classes yes and no ("there are" or "there are not"), where each single classification has four different possible outcomes shown in the confusion matrix for a binary classification of Table 1.
The average performance of the approach across the dataset (the performance for the dataset is reported in a confusion matrix).
CONFUSION MATRIX FOR GMM/SVM METHOD USING THE SHORT-TERM MFCC FEATURES IN FEMALE SPEAKERS.
The performance of each NN was measured by the confusion matrix obtained in the classification of the test samples (Congalton, 1991).
Table 2 shows the confusion matrix to present the results numerically.