A Novel DBSCAN Based on Binary Local Sensitive Hashing and Binary-KNN Representation

<table class="table-group" id="tab3"><tr><td><table class="table"><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td class="align_left">Dataset</td><td class="align_center">Object</td><td class="align_center">Dimension</td><td class="align_center">Label</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td class="align_left">Iris</td><td class="align_center">150</td><td class="align_center">4</td><td class="align_center">3</td></tr><tr><td class="align_left">Contraceptive Method Choice</td><td class="align_center">1437</td><td class="align_center">9</td><td class="align_center">3</td></tr><tr><td class="align_left">Letter Recognition</td><td class="align_center">20000</td><td class="align_center">16</td><td class="align_center">26</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Overview of the UCI datasets used in experiments.

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Table 3

Table 3: A Novel DBSCAN Based on Binary Local Sensitive Hashing and Binary-KNN Representation 