Results 41 to 50 of about 526,550 (191)
Robust Identification of Target Genes and Outliers in Triple-negative Breast Cancer Data [PDF]
, 2018 Correct classification of breast cancer sub-types is of high importance as it directly affects the therapeutic options. We focus on triple-negative breast cancer (TNBC) which has the worst prognosis among breast cancer types.
Casimiro, Sandra +4 more
core +2 more sources
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
Robust principal component analysis for accurate outlier sample detection in RNA-Seq data
BMC Bioinformatics, 2020 Background High throughput RNA sequencing is a powerful approach to study gene expression. Due to the complex multiple-steps protocols in data acquisition, extreme deviation of a sample from samples of the same treatment group may occur due to technical ...
Xiaoying Chen +4 more
doaj +1 more source
Subgroup and outlier detection analysis [PDF]
BMC Bioinformatics, 2013 Background High-dimensional biological data presents the opportunity to discover novel forms of biological heterogeneity, such as overexpression or suppression of expression of a particular gene in a subset of a cohort. This novel biological heterogeneity appears in the data as outliers or distinct subgroups.
Wu, Gang +5 more
openaire +1 more source
E-Jurnal Matematika, 2014 Multiple linear regression analysis with a lot of independent variable always makes many problems because there is a relationship between two or more independent variables.
NI WAYAN YULIANI +2 more
doaj +1 more source
Outlier Denoising Using a Novel Statistics-Based Mask Strategy for Compressive Sensing
Remote Sensing, 2023 Denoising is always an important step in seismic processing, in order to produce high-quality data for subsequent imaging and inversion. Different types of noise can be suppressed using targeted denoising methods.
Weiqi Wang +4 more
doaj +1 more source
A taxonomy framework for unsupervised outlier detection techniques for multi-type data sets [PDF]
, 2007 The term "outlier" can generally be defined as an observation that is significantly different from the other values in a data set. The outliers may be instances of error or indicate events.
Havinga, P.J.M. +2 more
core +1 more source
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
Outlier-resilient complexity analysis of heartbeat dynamics [PDF]
Scientific Reports, 2015 AbstractComplexity in physiological outputs is believed to be a hallmark of healthy physiological control. How to accurately quantify the degree of complexity in physiological signals with outliers remains a major barrier for translating this novel concept of nonlinear dynamic theory to clinical practice.
Lo, Men-Tzung +7 more
openaire +3 more sources
Mining Outlier Data in Mobile Internet-Based Large Real-Time Databases
Complexity, 2018 Mining outlier data guarantees access security and data scheduling of parallel databases and maintains high-performance operation of real-time databases.
Xin Liu, Yanju Zhou, Xiaohong Chen
doaj +1 more source