Results 71 to 80 of about 7,765,049 (335)
Optimal Feature Aggregation and Combination for Two-Dimensional Ensemble Feature Selection
Information, 2020 Feature selection is a way of reducing the features of data such that, when the classification algorithm runs, it produces better accuracy. In general, conventional feature selection is quite unstable when faced with changing data characteristics.
Machmud Roby Alhamidi, Wisnu Jatmiko
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Objective To evaluate the diagnostic yield and utility of universal paired tumor–normal multigene panel sequencing in newly diagnosed pediatric solid and central nervous system (CNS) tumor patients and to compare the detection of germline pathogenic/likely pathogenic variants (PV/LPVs) against established clinical referral criteria for cancer ...
Natalie Waligorski +9 more
wiley +1 more source
Entropy-based feature selection with applications to industrial internet of things (IoT) and breast cancer prediction [PDF]
Big Data and Computing VisionsFeature Selection (FS) is employed in the Machine Learning (ML) process to increase accuracy. Eliminating redundant and irrelevant variables while keeping the most important ones boosts the prediction capacity of the algorithms.
Ismail Mageed
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Purpose Although not always achieved, complete chemotherapy‐induced nausea and vomiting (CINV) control is the conventional goal of CINV prophylaxis. In this two‐center, mixed‐methods study, we sought to understand the preferences of adolescent patients and family caregivers for CINV control endpoints.
Haley Newman +8 more
wiley +1 more source
Binary Fox Optimization Algorithm for Feature Selection
Cybernetics and Information TechnologiesThere is an urgent need for algorithms capable of improving the selection of appropriate features that directly affect the improvement process of the algorithm’s accuracy efficiently. Therefore, in this paper, a new feature selection algorithm for binary
Mohammed Athraa Jasim +2 more
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Infinite Latent Feature Selection Technique for Hyperspectral Image Classification
Jurnal Elektronika dan Telekomunikasi, 2019 The classification process is one of the most crucial processes in hyperspectral imaging. One of the limitations in classification process using machine learning technique is its complexities, where hyperspectral image format has a thousand band that can
Tajul Miftahushudur +2 more
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Feature Redundancy Based on Interaction Information for Multi-Label Feature Selection
IEEE Access, 2020 Recent years, multi-label feature selection has gradually attracted significant attentions from machine learning, statistical computing and related communities and has been widely applied to diverse problems from music recognition to text mining, image ...
Wanfu Gao +3 more
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Special Issue “Algorithms for Feature Selection”
Algorithms, 2023 This Special Issue of the open access journal Algorithms is dedicated to showcasing cutting-edge research in algorithms for feature selection [...]
Muhammad Adnan Khan
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Feature and Variable Selection in Classification [PDF]
, 2014 The amount of information in the form of features and variables avail- able to machine learning algorithms is ever increasing. This can lead to classifiers that are prone to overfitting in high dimensions, high di- mensional models do not lend themselves
Karper, Aaron
core
Outcomes of Live Virus Vaccination in Patients With Vascular Anomalies Being Treated With Sirolimus
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Live vaccination in patients with vascular anomalies (VA) receiving sirolimus remains controversial due to immunosuppressive effects and theoretical risks. Procedure This single‐center retrospective study included patients with VA less than 4 years old at the start of sirolimus therapy who were incompletely vaccinated.
Svatava Merkle +5 more
wiley +1 more source