Towards Identify Selective Antibacterial Peptides Based on Abstracts Meaning

<table class="table-group" id="tab3"><tr><td><table class="table"><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left"> Correctly classified instances </td><td class="align_center"> 1762 (97.8889%) </td></tr><tr><td class="align_left"> Incorrectly classified instances </td><td class="align_center"> 38 (2.1111%) </td></tr><tr><td class="align_left"> Kappa statistic </td><td class="align_center"> 0.9666 </td></tr><tr><td class="align_left"> Mean absolute error </td><td class="align_center"> 0.0269 </td></tr><tr><td class="align_left"> Root mean squared error </td><td class="align_center"> 0.1161 </td></tr><tr><td class="align_left"> Relative absolute error </td><td class="align_center"> 6.3555</td></tr><tr><td class="align_left"> Root relative squared error </td><td class="align_center"> 25.2452</td></tr><tr><td class="align_left"> Total number of instances </td><td class="align_center"> 1800</td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Total average accuracy of classification is 97% and misclassification or error rate is 2.11%.

Computational and Mathematical Methods in Medicine

tab3

Table 3

Table 3: Towards Identify Selective Antibacterial Peptides Based on Abstracts Meaning 