[PDF] Accuracy Improvement of C4.5 using K means Clustering

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.

Analysis of Accuracy K-Means and Apriori Algorithms for Patient

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 ...