A Classification and Novel Class Detection Algorithm for Concept Drift Data Stream Based on the Cohesiveness and Separation Index of Mahalanobis Distance

<table class="table-group" id="tab2"><tr><td><table class="table"><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td class="align_left">Datasets</td><td class="align_center">Number of classes</td><td class="align_center">Number of dimensions</td><td class="align_center">Number of samples</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td class="align_left">KDD Cup 1999</td><td class="align_center">3</td><td class="align_center">23</td><td class="align_center">494021</td></tr><tr><td class="align_left">Covertype</td><td class="align_center">7</td><td class="align_center">54</td><td class="align_center">581012</td></tr><tr><td class="align_left">ArtificialCDS</td><td class="align_center">5</td><td class="align_center">27</td><td class="align_center">100000</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Parameter of different datasets.</div>

Journal of Electrical and Computer Engineering

tab2

Table 2

Table 2: A Classification and Novel Class Detection Algorithm for Concept Drift Data Stream Based on the Cohesiveness and Separation Index of Mahalanobis Distance 

Table 2 | A Classification and Novel Class Detection Algorithm for Concept Drift Data Stream Based on the Cohesiveness and Separation Index of Mahalanobis Distance 