Results 51 to 60 of about 23,619,888 (317)
Feature importance for machine learning redshifts applied to SDSS galaxies [PDF]
, 2015 We present an analysis of importance feature selection applied to photometric redshift estimation using the machine learning architecture Decision Trees with the ensemble learning routine Adaboost (hereafter RDF).
Hoyle, Ben +4 more
core +1 more source
A population-based statistical approach identifies parameters characteristic of human microRNA-mRNA interactions [PDF]
, 2004 BACKGROUND: MicroRNAs are ~17–24 nt. noncoding RNAs found in all eukaryotes that degrade messenger RNAs via RNA interference (if they bind in a perfect or near-perfect complementarity to the target mRNA), or arrest translation (if the binding is ...
Smalheiser, Neil R, Torvik, Vetle I
core +3 more sources
Outlier Detection for Welfare Analysis
, 2022 Extreme values are common in survey data and represent a recurring threat to the reliability of both poverty and inequality estimates. The adoption of a consistent criterion for outlier detection is useful in many practical applications, particularly when international and intertemporal ...
Belotti, Federico +2 more
openaire +2 more sources
Election Law Journal, 2018 The prospect of convincing courts to intervene in partisan gerrymandering has inspired a great deal of research and, recently, public attention. But how can neutral parties such as courts and independent redistricting commissions discern when a district ...
Gowri Ramachandran, Dara Gold
semanticscholar +1 more source
Molecular Oncology, EarlyView.This study indicates that Merkel cell carcinoma (MCC) does not originate from Merkel cells, and identifies gene, protein & cellular expression of immune‐linked and neuroendocrine markers in primary and metastatic Merkel cell carcinoma (MCC) tumor samples, linked to Merkel cell polyomavirus (MCPyV) status, with enrichment of B‐cell and other immune cell
Richie Jeremian +10 more
wiley +1 more source
Early identification of scientific breakthroughs through outlier analysis based on research entities
Journal of Data and Information ScienceTo address the “anomalies” that occur when scientific breakthroughs emerge, this study focuses on identifying early signs and nascent stages of breakthrough innovations from the perspective of outliers, aiming to achieve early identification of ...
Zhao Yang +3 more
doaj +1 more source
An Incremental Local Outlier Detection Method in the Data Stream
Applied Sciences, 2018 Outlier detection has attracted a wide range of attention for its broad applications, such as fault diagnosis and intrusion detection, among which the outlier analysis in data streams with high uncertainty and infinity is more challenging.
Haiqing Yao +3 more
doaj +1 more source
Outlier Analysis of Categorical Data using NAVF [PDF]
Informatică economică, 2013 Outlier mining is an important task to discover the data records which have an exceptional behavior comparing with other records in the remaining dataset. Outliers do not follow with other data objects in the dataset.
D. LAKSHMI SREENIVASA REDDY +2 more
doaj +1 more source
Multivariate Outlier Detection in Applied Data Analysis: Global, Local, Compositional and Cellwise Outliers [PDF]
Mathematical Geosciences, 2020 AbstractOutliers are encountered in all practical situations of data analysis, regardless of the discipline of application. However, the term outlier is not uniformly defined across all these fields since the differentiation between regular and irregular behaviour is naturally embedded in the subject area under consideration. Generalized approaches for
Peter Filzmoser, Mariella Gregorich
openaire +1 more source
A Monte Carlo-Based Outlier Diagnosis Method for Sensitivity Analysis
Remote Sensing, 2020 An iterative outlier elimination procedure based on hypothesis testing, commonly known as Iterative Data Snooping (IDS) among geodesists, is often used for the quality control of modern measurement systems in geodesy and surveying.
V. F. Rofatto +4 more
semanticscholar +1 more source