Skip to main content
. 2020 May 15;62(3):273–282. doi: 10.4103/psychiatry.IndianJPsychiatry_91_20

Supplementary Table 2.

Different performance measures used for evaluation of support vector machine classifier

Measure Description Mathematical expression
Accuracy Percentage of correctly classified samples graphic file with name IJPsy-62-273-g009.jpg
Sensitivity Percentage of correctly classified samples belonging to schizophrenia (experiment 1)/positive symptoms (experiment 2) graphic file with name IJPsy-62-273-g010.jpg
Specificity Percentage of correctly classified samples belonging to the healthy group (experiment 1)/positive symptoms (experiment 2) graphic file with name IJPsy-62-273-g011.jpg
Area under receiver operating characteristic curve A common measure of sensitivity and specificity graphic file with name IJPsy-62-273-g012.jpg

tp – True positives (number of correctly classified positive samples), tn – True negatives (number of correctly classified negative samples), fp – False positives (number of wrongly classified positive samples), fn – False negatives (number of wrongly classified negative samples). In experiment 1 – Schizophrenia was considered as positive group and healthy was considered as negative group. In experiment 2 – Positive symptom was considered as positive group and negative symptom was considered as negative group. SVM – Support vector machine; AUC – Area under receiver operating curve