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PYTHON MÜHİTİNDƏ K-MEANS, K-MEANS++ VƏ MİNİ BATCH K-MEANS ALQORİTMLƏRİNİN MÜQAYİSƏLİ ANALİZİ
Problems of Information Technology, 2021 Məqalədə k-means alqortitmi və onun modifikasiyalarının Python mühitində müxtəlif ölçülü verilənlərə tətbiqi məsələlərinə baxılır. Eyni zamanda ənənəvi k-means klasterləşdirmə alqoritmi və onun modifikasıyalarının mövcud vəziyyəti, imkanları, çatışmazlıqları, meydana çıxan problemlər tədqiq edilmiş və onların həlli üçün təkliflər verilmişdir. k-means++
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Reducing the Time Requirement of k-Means Algorithm [PDF]
, 2012 Traditional k-means and most k-means variants are still computationally expensive for large datasets, such as microarray data, which have large datasets with large dimension size d.
Adebiyi, E. F. +3 more
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, 2018 The recent framework of compressive statistical learning aims at designing tractable learning algorithms that use only a heavily compressed representation-or sketch-of massive datasets.
Jacques, Laurent, Schellekens, Vincent
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Penggunaan N-mers Frequency pada Analisis Barisan DNA
Jambura Journal of Mathematics, 2020 Salah satu metode untuk menganalisis barisan DNA adalah menggunaan N-mers Frequency. N-mers Frequency termasuk metode data mining pada barisan DNA, dimana barisan DNA yang merupakan data string “ACGT” akan diubah menjadi data numerik.
Khoirul Umam, Rahmat Sagara
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Journal of Statistical Computation and Simulation, 2017 Traditionally, practitioners initialize the {\tt k-means} algorithm with centers chosen uniformly at random. Randomized initialization with uneven weights ({\tt k-means++}) has recently been used to improve the performance over this strategy in cost and run-time.
Yoder, Jordan, Priebe, Carey E.
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Embed and Conquer: Scalable Embeddings for Kernel k-Means on MapReduce [PDF]
, 2014 The kernel $k$-means is an effective method for data clustering which extends the commonly-used $k$-means algorithm to work on a similarity matrix over complex data structures.
Elgohary, Ahmed +3 more
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Assessing Cloud Segmentation in the Chromacity Diagram of All-Sky Images
Remote Sensing, 2020 All-sky imaging systems are currently very popular. They are used in ground-based meteorological stations and as a crucial part of the weather monitors for autonomous robotic telescopes. Data from all-sky imaging cameras provide important information for
Lukáš Krauz +3 more
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The Monongahela tradition in "real time": Bayesian analysis of radiocarbon dates.
PLoS ONE, 2022 Despite advances in techniques, methods, and theory, northeastern North American archaeologists continue to use early to mid-twentieth century culture historical taxa as units of analysis and narrative.
John P Hart, Bernard K Means
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Applied Sciences, 2023 Diversified noise sources pose great challenges in the engineering of an ANC (active noise control) system design. To solve this problem, this paper proposes an ANC method based on VMD (variational mode decomposition) and Ensemble Learning.
Xiaobei Liang +4 more
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RSKC: An R Package for a Robust and Sparse K-Means Clustering Algorithm
Journal of Statistical Software, 2016 Witten and Tibshirani (2010) proposed an algorithim to simultaneously find clusters and select clustering variables, called sparse K-means (SK-means).
Yumi Kondo +2 more
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