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A variance-guided resampling framework for better K-medoids clustering [PDF]
MethodsXOne of the limitations of the k-medoids clustering algorithm is its susceptibility to local optimization and the potential for identical or similar objects to be assigned to different initial clusters.
Kariyam, Feri Wijayanto, Edy Widodo
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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, Weksi Budiaji
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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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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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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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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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International Journal of Distributed Sensor Networks, 2021 The tremendous growth of Internet of Medical Things has led to a surge in medical user data, and medical data publishing can provide users with numerous services. However, neglectfully publishing the data may lead to severe leakage of user’s privacy.
Zekun Zhang +3 more
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Sistemasi: Jurnal Sistem Informasi, 2022 Nowadays, e-commerce data transactions are commonly used by companies to provide new information. The data transaction can reveal customer segmentation or groups based on the similar characteristics and behavior of each customer.
Romadansyah Siagian +2 more
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