Results 11 to 20 of about 10,133,028 (343)
Balanced Clustering with Least Square Regression
AAAI Conference on Artificial Intelligence, 2017 Clustering is a fundamental research topic in data mining. A balanced clustering result is often required in a variety of applications. Many existing clustering algorithms have good clustering performances, yet fail in producing balanced clusters. In
Hanyang Liu +3 more
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Approximate least squares [PDF]
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014 Preprint of the paper submitted to IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP ...
Michael Lunglmayr +2 more
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Partitioned least squares [PDF]
Machine Learning, 2019 AbstractLinear least squares is one of the most widely used regression methods in many fields. The simplicity of the model allows this method to be used when data is scarce and allows practitioners to gather some insight into the problem by inspecting the values of the learnt parameters.
Roberto Esposito +2 more
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Noise Reduction in RTL-SDR using Least Mean Square and Recursive Least Square
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2020 Noise reduction is an important process in a communication system, one of which is radio communication. In the process of broadcasting radio Frequency Modulation (FM) often encountered noise so that listeners find it difficult to understand the ...
Aviv Yuniar Rahman +2 more
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Identifikasi Motor DC dengan Metode Recursive Least Square
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems), 2021 Motor DC Minertia tipe UGTMEM-03STC25 merupakan salah satu alat di Laboratorium Sistem Kontrol Universitas Brawijaya Malang. Dengan menggunakan metode RLS motor DC Minertia tipe UGTMEM-03STC25 diperoleh model terbaik adalah orde 4 dengan parameter a1 ...
Muhammad Aziz Muslim +2 more
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Distributed average consensus with least-mean-square deviation
Journal of Parallel and Distributed Computing, 2007 Stephen Boyd, Seung-Jean Kim
exaly +2 more sources
Least-Square Approximation for a Distributed System [PDF]
Journal of Computational And Graphical Statistics, 2019 In this work, we develop a distributed least-square approximation (DLSA) method that is able to solve a large family of regression problems (e.g., linear regression, logistic regression, and Cox’s model) on a distributed system.
Xuening Zhu, Feng Li, Hansheng Wang
semanticscholar +1 more source
گۆڤارا زانستێن مرۆڤایەتی یا زانكۆیا زاخۆ, 2022 This paper was dealing with variables for MAS Cement Factory where evince many problems , more than one variable dependent and presence the problem of multicollinearity and so presence the correlation between the predictive variables and the dependent ...
Sherin mohyaldeen, Mohammed Alhassawy
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Unifying Least Squares, Total Least Squares and Data Least Squares [PDF]
, 2002 The standard approaches to solving overdetermined linear systems A x ≈ b construct minimal corrections to the vector b and/or the matrix A such that the corrected system is compatible. In ordinary least squares (LS) the correction is restricted to b, while in data least squares (DLS) it is restricted to A. In scaled total least squares (Scaled TLS) [15]
Christopher C. Paige, Zdeněk Strakoš
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A new modified Kies Fréchet distribution: Applications of mortality rate of Covid-19
Results in Physics, 2021 The purpose of this paper is to identify an effective statistical distribution for examining COVID-19 mortality rates in Canada and Netherlands in order to model the distribution of COVID-19.
Anum Shafiq +5 more
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