Results 31 to 40 of about 2,006,480 (313)
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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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++
openaire +1 more source
Clustering with Spectral Norm and the k-means Algorithm [PDF]
, 2010 There has been much progress on efficient algorithms for clustering data points generated by a mixture of $k$ probability distributions under the assumption that the means of the distributions are well-separated, i.e., the distance between the means of ...
Kannan, Ravindran, Kumar, Amit
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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
doaj +1 more source
, 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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Privacy-Preserving and Outsourced Multi-User k-Means Clustering [PDF]
, 2014 Many techniques for privacy-preserving data mining (PPDM) have been investigated over the past decade. Often, the entities involved in the data mining process are end-users or organizations with limited computing and storage resources.
Bertino, Elisa +4 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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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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Faster K-Means Cluster Estimation
, 2017 There has been considerable work on improving popular clustering algorithm `K-means' in terms of mean squared error (MSE) and speed, both. However, most of the k-means variants tend to compute distance of each data point to each cluster centroid for ...
A Likas, DT Pham, SP Lloyd, T Kanungo
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