An empirical evaluation of k-means clustering technique and comparison
In this research work we have studied the behavior of k-means clustering technique and we
have made an analysis. We have mentioned the limitations and some methods to improve it …
have made an analysis. We have mentioned the limitations and some methods to improve it …
An automatic text classification system based on genetic algorithm
The increasing numbers of on-line text documents make the process of searching and
accessing documents related to a specific category a very difficult task. By classifying the …
accessing documents related to a specific category a very difficult task. By classifying the …
[PDF][PDF] Penentuan Prioritas Penerima Dana Bantuan Operasional Pendidikan Lembaga Pendidikan Anak Usia Dini dengan Metode KNN, TOPSIS dan K-Means
ABSTRACT Education Operational Aid of the Early Childhood Education unit is the financial
assistance which is provided to educational institutions, especially for those who engaged in …
assistance which is provided to educational institutions, especially for those who engaged in …
[PDF][PDF] Targeted ranking-based clustering using AHP K-means
K-Means can group similar objects features into specified number (K) of cluster centers
region. Similarity is measured based on their closest distance of multiple features coordinate …
region. Similarity is measured based on their closest distance of multiple features coordinate …
Towards Fully Autonomous Clustering
C Li - 2022 - search.proquest.com
My Ph. D. thesis topic is Machine Learning and focuses on Clustering Technologies:
Towards Autonomous Clustering. Machine learning is a method of data analysis that …
Towards Autonomous Clustering. Machine learning is a method of data analysis that …
Reliability analysis based on optimal location partition of communication network
RHH Al-Elayawi - 2022 - acikerisim.gelisim.edu.tr
Clustering a network enables the individuals to separate the network in to number of
subnetworks. K-mean clustering is one of the most well-known clustering techniques, known …
subnetworks. K-mean clustering is one of the most well-known clustering techniques, known …
[PDF][PDF] Performance Evaluation of Three Unsupervised Clustering Algorithms
R Baruri, A Ghosh - academia.edu
Clustering is a ubiquitous technique in machine learning. Clustering is useful when we do
not have labeled data. In the present study, three of the most useful and easy to implement …
not have labeled data. In the present study, three of the most useful and easy to implement …
A Real-Time Atypical Amplitude Detection based on Measurement Metadata
PAbMM is a data stream engine which implements a real-time data processing strategy
focused on the Measurement and Evaluation (M&E) projects. This allows an active …
focused on the Measurement and Evaluation (M&E) projects. This allows an active …
[PDF][PDF] A hybrid model of ordinal ranking-based clustering using G+ Rank K-Means
K-Means is a clustering technique that maps object features onto multidimensional
coordinates and groups them based on location closeness. However, measuring closest …
coordinates and groups them based on location closeness. However, measuring closest …