An improved K-means algorithm with meliorated initial center

Chen, Guangping; Wang, Wenpeng

doi:10.1109/iccse.2012.6295047

Cited by 4 publications

(4 citation statements)

References 6 publications

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“…In the next stage, the center point is used in calculations with the kmeans algorithm. This study concludes that calculations with improved km-means produce better center points and have a higher accuracy level than traditional k-means [13].…”

Section: Introductionmentioning

confidence: 65%

“…Calculate the distance between objects 𝑥𝑖 and 𝑥𝑗 with object data in cluster M. If object data in cluster M has a minimum distance to object data𝑥 𝑖 , then the data is included in cluster X. If the object data in cluster M has a minimum distance to the object data𝑥 𝑗 , then the data is included in cluster Y [13].…”

Section: Improved K-means Clusteringmentioning

confidence: 99%

“…The K-Means methods are clustering methods usually used by several previous researchers, and they have been implemented especially in the education field [12]- [13]. Meanwhile, agglomerative methods have also been applied to group data by a number of earlier researchers [16]- [18], which, in certain case studies performs and is more accurate than K-Means [19].…”

Section: Introductionmentioning

confidence: 99%

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A Comparative Study of Students Graduation Analysis Using Classification Methods in Undergraduate Electrical Engineering Tidar University

Wicaksono,

Nisworo,

Nata

2024

j. Teknik inform.

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This research aimed to classify achievement factors for electrical engineering students at Tidar University using K-Means and Agglomerative Clustering classification algorithms. The goal was to understand if any parameters influence high-achieving student performance. The Indonesian government and private sector for university students provide significant education funds. Student scholarships are awarded based primarily on GPA and entry path, overburdening staff and causing confusion during distribution to eligible recipients. A system was needed to accommodate additional eligible criteria. The researcher selected factors to identify engineering student performance, including school origin, entry path, tuition fees, and GPA. These inputs could determine graduation status. The results compared calculation methods based on collected data accuracy, processing times, and characterizing clustered data to determine the best classification method. Agglomerative Hierarchical Clustering performed better. Accuracy testing on 600 training data points yielded 73.94% for improved K-means and 90.42% for AHC. The Average processing time was 674.92 seconds for improved K-means and 554.35 seconds for AHC. Silhouette testing also characterized calculation methods, with improved K-means scoring best at 0.654 and AHC at 0.787 using two clusters.

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Section: Introductionmentioning

confidence: 65%

Section: Improved K-means Clusteringmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Comparative Study of Students Graduation Analysis Using Classification Methods in Undergraduate Electrical Engineering Tidar University

Wicaksono,

Nisworo,

Nata

2024

j. Teknik inform.

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“…Pada metode k-means, pencarian titik pusat awal dilakukan dengan cara acak. Namun pada improved k-means, dilakukan modifikasi pada tahapan algoritma dengan menambahkan beberapa tahapan dalam pencarian titik pusat awal sehingga titik pusat awal ditemukan tanpa pengacakan [13]. Berikut merupakan langkah-langkah dalam algoritma improved k-means:…”

Section: Improved K-meansunclassified

Implementasi Metode Improved K-Means dengan Algoritma Dbscan untuk Pengelompokan Film

Muhajir

Sari

2020

UJMC

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The Indonesian film industry continues to experience an increase seen from the number of films that appear in theaters today with a box office increase of 28 percent each year in the past four years. Internet Movie Database (IMDb) is a website that provides information about films around the world, including the people involved in it from actors, directors, writers to makeup artists and soundtracks. In this case the researcher wants to conduct research on the characteristics of the film and the factors that make a film to be included in the IMDb Top 250. The data used in this study uses scraped data from the website. The method used is a non-hierarchical clustering method, namely kmeans and Dbscan. Where the Dbscan algorithm is used to determine the optimum number of clusters then proceed by grouping data based on centroids with k-means algorithm. From the analysis it was found that the factors that could influence a film included in the IMDB Top 250 were duration, number of votes, and films directed by Rajkumar Hirani and the optimal number of clusters using Dbscan algorithm obtained six clusters. With the improved k-means algorithm, the accuracy value for the cluster results is 87.2%.

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Cluster Analysis based on HDWA-Kmeans Algorithm Assisted Identification of Poor Students

2022

2022 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)

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An improved K-means algorithm with meliorated initial center

Cited by 4 publications

References 6 publications

A Comparative Study of Students Graduation Analysis Using Classification Methods in Undergraduate Electrical Engineering Tidar University

A Comparative Study of Students Graduation Analysis Using Classification Methods in Undergraduate Electrical Engineering Tidar University

Implementasi Metode Improved K-Means dengan Algoritma Dbscan untuk Pengelompokan Film

Cluster Analysis based on HDWA-Kmeans Algorithm Assisted Identification of Poor Students

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