Results 61 to 70 of about 88,907 (241)
Feature Selection with the Boruta Package
Journal of Statistical Software, 2010 This article describes a R package Boruta, implementing a novel feature selection algorithm for finding emph{all relevant variables}. The algorithm is designed as a wrapper around a Random Forest classification algorithm.
Miron B. Kursa, Witold R. Rudnicki
doaj
Ranking Feature Importance Objectives for Explainable Classification
IEEE AccessRecent studies on explainable machine learning models often analyse feature importance after training, but this results in a model that does not capture feature dependencies and requires extra computational resources for explainability.
Pragya Gupta +4 more
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Molecular Oncology, EarlyView.Development of therapies targeting cancer‐associated fibroblasts (CAFs) necessitates preclinical model systems that faithfully represent CAF–tumor biology. We established an in vitro coculture system of patient‐derived pancreatic CAFs and tumor cell lines and demonstrated its recapitulation of primary CAF–tumor biology with single‐cell transcriptomics ...
Elysia Saputra +10 more
wiley +1 more source
Melt Instability Identification Using Unsupervised Machine Learning Algorithms
Macromolecular Materials and Engineering, 2023 In industrial extrusion processes, increasing shear rates can lead to higher production rates. However, at high shear rates, extruded polymers and polymer compounds often exhibit melt instabilities ranging from stick‐slip to sharkskin to gross melt ...
Alex Gansen +5 more
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Detect influential points of feature rankings
Computational Biology and ChemistryBackground Deriving feature rankings is essential in bioinformatics studies since the ordered features are important in guiding subsequent research. Feature rankings may be distorted by influential points (IP), but such effects are rarely mentioned in previous studies.
Shuo Wang, Junyan Lu
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The Feature Importance Ranking Measure [PDF]
, 2009 15 pages, 3 figures. to appear in the Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD ...
Zien, A. +3 more
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Molecular Oncology, EarlyView.The noncoding region of the genome plays a key role in regulating gene expression, and mutations within these regions are capable of altering it. Researchers have identified multiple functional noncoding mutations associated with increased cancer risk in the genome of breast cancer patients.
Arnau Cuy Saqués +3 more
wiley +1 more source
Molecular Oncology, EarlyView.We developed and validated a DNA methylation–based biomarker panel to distinguish pleural mesothelioma from other pleural conditions. Using the IMPRESS technology, we translated this panel into a clinically applicable assay. The resulting two classifier models demonstrated excellent performance, achieving high AUC values and strong diagnostic accuracy.
Janah Vandenhoeck +12 more
wiley +1 more source
An Empirical Study on the Effectiveness of Feature Selection for Cross-Project Defect Prediction
IEEE Access, 2019 Software defect prediction has attracted much attention of researchers in software engineering. At present, feature selection approaches have been introduced into software defect prediction, which can improve the performance of traditional defect ...
Qiao Yu +4 more
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Molecular Oncology, EarlyView.We developed a cost‐effective methylation‐specific droplet digital PCR multiplex assay containing tissue‐conserved and tumor‐specific methylation markers. The assay can detect circulating tumor DNA with high accuracy in patients with localized and metastatic colorectal cancer.
Luisa Matos do Canto +8 more
wiley +1 more source