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Difference between revisions of "Anomaly Detection Tool Test Cases"
(→Test Case 1) |
(→Test Case 2) |
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== Test Case 2 == | == Test Case 2 == | ||
+ | * No. of clusters: 2 | ||
+ | * No. of data points: 1000 | ||
+ | * Data points are not easily separable into 2 clusters as depicted in Fig.2. | ||
+ | |||
== Test Case 3 LOF Test case == | == Test Case 3 LOF Test case == | ||
== Test Case 4 100 data points == | == Test Case 4 100 data points == | ||
== Test Case 5 100 data points == | == Test Case 5 100 data points == | ||
== Test Case 6 LOF Test case: 100 data points == | == Test Case 6 LOF Test case: 100 data points == |
Revision as of 18:41, 26 February 2015
Contents
Test Case 1
- No. of clusters: 2
- No. of Data points: 1000
- Data points are easily separable into 2 clusters as depicted in Fig.1. Kmeans clustering algorithm can easily identify two distinct clusters in this case.
Test Case 2
- No. of clusters: 2
- No. of data points: 1000
- Data points are not easily separable into 2 clusters as depicted in Fig.2.