Comparison of Different Distance Functions in Document Clustering |
Author(s): |
| Richa Gupta , Ambala College of Engineering & Applied Research Affiliated to Kurukshetra University; Manjit Singh, Ambala College of Ebgineering & Applied Research |
Keywords: |
| Adaboost, Query learning, Precision and Recall, Strong Classifier, Weak Classifier |
Abstract |
|
This paper provides the comparison of different distance functions like squared euclidean, cityblock, cosine, pearson correlation & hamming distances. K- Means clustering algorithm is used to make the comparison of different distance functions. The results obtained are validated with the help of Silhouette Coefficient. We found out that there is a variation in the results provided by different functions. |
Other Details |
|
Paper ID: IJSRDV3I41016 Published in: Volume : 3, Issue : 4 Publication Date: 01/07/2015 Page(s): 1807-1810 |
Article Preview |
|
|
|
|
