Results 21 to 30 of about 188,394 (267)

THE USE OF STATISTICAL CRITERIA FOR EVALUATION TEST OF DATA ON PROPERTIES OF INORGANIC SUBSTANCES

open access: yesТонкие химические технологии, 2017
Three statistical criteria were compared on the basis of the sampling of chemical data in the article. When the criteria were compared, the level of significance was taken as equal to 0.05, because this value is most often used in the technical ...
I. D. Tarasenko, V. A. Dudarev
doaj   +1 more source

OUTLIER DETECTION TECHNIQUE USING CT-OCSVM AND FUZZY RULE-BASED SYSTEM IN WIRELESS SENSOR NETWORKS

open access: yesJournal of Engineering and Sustainable Development, 2020
The development of Wireless Sensor Networks (WSNs) has been attained in the past few years due to its important using in wide range of application. The readings of data derived from WSN nodes are not always accurate and may contain abnormal data.
Hussein Hassan Shia   +2 more
doaj   +1 more source

Memorable outliers [PDF]

open access: yesCurrent Biology, 2013
SummaryReports of photographic memory are widespread but the search for truly extraordinary memory abilities has uncovered only a handful of examples. But the fact that such individuals exist has fascinated and begs the question, what is the source of such abilities? Cyrus Martin reports.
openaire   +2 more sources

Subspace Approximation with Outliers [PDF]

open access: yes, 2020
The subspace approximation problem with outliers, for given $n$ points in $d$ dimensions $x_{1},\ldots, x_{n} \in R^{d}$, an integer $1 \leq k \leq d$, and an outlier parameter $0 \leq α\leq 1$, is to find a $k$-dimensional linear subspace of $R^{d}$ that minimizes the sum of squared distances to its nearest $(1-α)n$ points.
Amit Deshpande 0001, Rameshwar Pratap
openaire   +2 more sources

Weighted fast-trimmed likelihood estimator for mixture regression models

open access: yesFrontiers in Applied Mathematics and Statistics
The fast-trimmed likelihood estimate is a robust method to estimate the parameters of a mixture regression model. However, this method is vulnerable to the presence of bad leverage points, which are outliers in the direction of independent variables.
Hassan S. Uraibi, Mohammed Qasim Waheed
doaj   +1 more source

Assessing Steady-State, Multivariate Experimental Data Using Gaussian Processes: The GPExp Open-Source Library

open access: yesEnergies, 2016
Experimental data are subject to different sources of disturbance and errors, whose importance should be assessed. The level of noise, the presence of outliers or a measure of the “explainability” of the key variables with respect to the externally ...
Sylvain Quoilin, Jessica Schrouff
doaj   +1 more source

Analysis of Stylometric Features and Segmentation Strategies in Intrinsic Plagiarism Detection System

open access: yesJurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2020
Two different paradigms in the field of plagiarism detection resulting in External Plagiarism Detection (EPD) and Intrinsic Plagiarism Detection (IPD) systems.
Sylvia Putri Gunawan   +2 more
doaj   +1 more source

Phase Angle as an Early Functional Biomarker of Cancer‐Related Fatigue in Pediatric Oncology: A Prospective Longitudinal Study

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background Pediatric cancer remains a leading cause of morbidity and mortality worldwide, particularly in low‐and middle‐income countries. Cancer treatment may impair nutritional status, alter body composition, and exacerbate cancer‐related fatigue (CRF).
Luís Carlos Lopes‐Junior   +11 more
wiley   +1 more source

Optimasi Algoritma K-Nearest Neighbors Berdasarkan Perbandingan Analisis Outlier (Berbasis Jarak, Kepadatan, LOF)

open access: yesJurnal Nasional Teknik Elektro dan Teknologi Informasi
Pertumbuhan data yang terjadi saat ini berpengaruh terhadap analisis data di berbagai bidang, seperti astronomi, bisnis, kedokteran, pendidikan, dan finansial.
Fitri Ayuning Tyas   +2 more
doaj   +1 more source

Breakdown Point of Robust Support Vector Machines

open access: yesEntropy, 2017
Support vector machine (SVM) is one of the most successful learning methods for solving classification problems. Despite its popularity, SVM has the serious drawback that it is sensitive to outliers in training samples.
Takafumi Kanamori   +2 more
doaj   +1 more source

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