A new Initial Centroid finding Method based on Dissimilarity Tree for
find the better initial centroid as well as every bit more accurate cluster with enhance the efficiency and accuracy of K-means clustering algorithms.
Mine Blood Donors Information through Improved K- Means Clustering
show that improved K-means algorithm produces accurate clusters in less computation time to find the donors information. Keywords. Clustering means
Rapid cell population identification in flow cytometry data
16 déc. 2010 We have developed flowMeans a time-efficient and accurate method for automated ... The K-means clustering algorithm was the first automated.
Outlier Detection and Removal Algorithm in K-Means and
30 août 2017 K-Means and Hierarchical clustering on a data set then find ... to remove those outliers and maximize the accuracy of clustering.
Improving the Performance of K-Means Clustering For High
Hence to improve the efficiency and accuracy of mining task on high dimensional data the data must be preprocessed by efficient dimensionality reduction
Bisecting K-means Algorithm Based on K-valued Self- determining
Key words: Bisecting k-means K
Performance Evaluation of K-Means and Heirarichal Clustering in
In this paper we have used weka data mining tool version. 3.7 for testing accuracy and running time of simple K- means and Hierarchical clustering algorithm on
Accuracy Improvement of C4.5 using K means Clustering
target attribute of test data correctly from the knowledge gained from the variable with higher accuracy level with the help of K means clustering which ...
Adaptation of K-Means Clustering Algorithm for Collaborative
user/items to find neighbors within a subset of clustered data for more accurate than the K-means clustering algorithm but not efficient due to its time ...
