Results 1 to 10 of about 4,694 (162)
BarekengK-Medoids is a clustering algorithm that is often used because of its robustness against outliers. In this research, the focus is to cluster provinces based on educational level through several assessment indicators.
Octavia Rahmawati, Achmad Fauzan
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Prediction of cold chain loading environment for agricultural products based on K-medoids-LSTM-XGBoost ensemble model [PDF]
PeerJ Computer ScienceCold chain loading is a crucial aspect in the process of cold chain transportation, aiming to enhance the quality, reduce energy consumption, and minimize costs associated with cold chain logistics.
Zhijie Luo +4 more
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Simple K-Medoids Partitioning Algorithm for Mixed Variable Data
Algorithms, 2019 A simple and fast k-medoids algorithm that updates medoids by minimizing the total distance within clusters has been developed. Although it is simple and fast, as its name suggests, it nonetheless has neglected local optima and empty clusters that may ...
Friedrich Leisch +2 more
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BanditPAM++: Faster $k$-medoids Clustering
CoRR, 2023 Clustering is a fundamental task in data science with wide-ranging applications. In $k$-medoids clustering, cluster centers must be actual datapoints and arbitrary distance metrics may be used; these features allow for greater interpretability of the cluster centers and the clustering of exotic objects in $k$-medoids clustering, respectively.
Mo Tiwari +6 more
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Penerapan Metode K-Medoids untuk Pengelompokan Mahasiswa Berpotensi Drop Out
Jurnal Teknologi Informasi dan Ilmu Komputer, 2023 Drop out merupakan penghentian atau pemutusan hubungan studi mahasiswa di perguruan tinggi, hal ini disebabkan oleh beberapa hal yang telah ditentukan oleh universitas. Perguruan tinggi dapat membuat kebijakan guna meminimalkan jumlah mahasiswa drop out
Syamsul Bahri, Dwi Marisa Midyanti
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JSiI (Jurnal Sistem Informasi), 2022 Penyebaran yang cukup luas dan cepat, membuat pandemi Covid-19 di Sumatera Selatan berdampak negatif pada semua sektor seperti kesehatan, pekerjaan dan perekonomian.
Sevi Dian Nirwana +2 more
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Comparison of K-Medoids Method and Analytical Hierarchy Clustering on Students' Data Grouping
JOIV: International Journal on Informatics Visualization, 2023 One sign of how successfully the educational process is carried out on campus in a university is the timely graduation of students. This study compares the Analytic Hierarchy Clustering (AHC) approach with the K-Medoids method, a data mining technique ...
Lisna Zahrotun +4 more
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Parallelization of Partitioning Around Medoids (PAM) in K-Medoids Clustering on GPU
Knowledge Engineering and Data Science, 2020 K-medoids clustering is categorized as partitional clustering. K-medoids offers better result when dealing with outliers and arbitrary distance metric also in the situation when the mean or median does not exist within data.
Adhi Prahara +2 more
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Energy Strategy Reviews, 2023 The adverse effects of coal and gas energy production with the subsequent rapid increase in energy consumption emphasize the importance for Australia to adopt more renewable energy sources to counteract these dismissive contributions to climate change ...
Rain Holloway +6 more
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Anchored k-medoids: a novel adaptation of k-medoids further refined to measure long-term instability in the exposure to crime [PDF]
Journal of Computational Social Science, 2021 AbstractLongitudinal clustering techniques are widely deployed in computational social science to delineate groupings of subjects characterized by meaningful developmental trends. In criminology, such methods have been utilized to examine the extent to which micro places (such as streets) experience macro-level police-recorded crime trends in unison ...
Monsuru Adepeju +2 more
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