Results 71 to 80 of about 9,444,467 (301)
Exploring Kernel Machines and Support Vector Machines: Principles, Techniques, and Future Directions
The kernel method is a tool that converts data to a kernel space where operation can be performed. When converted to a high-dimensional feature space by using kernel functions, the data samples are more likely to be linearly separable.
Ke-Lin Du +4 more
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AGE ESTIMATION WITH REGARD FOR CLASSIFIABLE ABILITY OF EACH COMPONENT IN REDUCED DIMENSION AGE MANIFOLD [PDF]
A new age estimation method that takes classifiable ability of each component in age manifold into account is considered. First, we analysis the age classification rate of each component in reduced dimension age manifold.
Pak Duho, Ri Kumhyok, Hyon Cungyong
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Minimal Support Vector Machine
Support Vector Machine (SVM) is an efficient classification approach, which finds a hyperplane to separate data from different classes. This hyperplane is determined by support vectors. In existing SVM formulations, the objective function uses L2 norm or L1 norm on slack variables. The number of support vectors is a measure of generalization errors. In
Shuai Zheng 0002, Chris Ding
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Tutorial on Support Vector Machines [PDF]
Abstract The aim of this tutorial is to help students grasp the theory and applicability of support vector machines (SVMs). The contribution is an intuitive style tutorial that helped students gain insights into SVM from a unique perspective. An internet search will reveal many videos and articles on SVM, but free peer-reviewed tutorials are ...
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Loss of eIF5A rewires thapsigargin‐mediated endoplasmic reticulum stress responses in multiple myeloma cells by selective translation of mRNA transcripts, consequently dampening thapsigargin‐induced unfolded protein response (UPR) activation and shifting the balance from induction of apoptosis toward cell survival and proliferation.
Demi Both +7 more
wiley +1 more source
Circulating microRNA profiles distinguish nonmalignant Lynch syndrome from cancer‐associated Lynch syndrome, sporadic colorectal cancer, and healthy controls. Age‐stratified analysis reveals disease‐specific regulatory states, and a six‐miRNA panel shows concordant separation in an independent colorectal tissue cohort.
Ramadhani Salum Chambuso +5 more
wiley +1 more source
The impact of leukocyte‐associated RNA retention on platelet RNA‐based cancer detection
Platelets carry RNA signals that may help detect cancer, but platelet samples can also retain RNA from white blood cells. We found that this retained white blood cell signal did not significantly affect machine learning cancer classification, suggesting that the cancer‐related RNA signal in platelets is largely independent of leukocyte‐associated RNA ...
Michał Sieczczyński +12 more
wiley +1 more source
Versatile vector tools for efficient protein screening across multiple expression systems
A unified vector toolkit enables rapid protein expression screening across E. coli, insect, and mammalian cells. A single primer pair amplifies the target gene, which is inserted into any vector via a standardized interface. This streamlined workflow eliminates repeated cloning steps, accelerating the identification of optimal expression conditions for
Zhimin Zhu +5 more
wiley +1 more source
LINEX Support Vector Machine for Large-Scale Classification
Traditional soft margin support vector machine usually uses hinge loss to build a classifier with the “maximum-margin” principle. However, C-SVM depends on support vectors causing the loss of data information.
Yue Ma +3 more
doaj +1 more source
Loss of AMBRA1 activates MAPK and angiogenesis signaling pathways in melanoma cells
Loss of AMBRA1 in melanoma cells activates multiple oncogenic pathways associated with tumor progression. Transcriptomic and protein network analyses revealed that AMBRA1 depletion enhances MAPK/ERK signaling, angiogenesis, TGF‐β/EMT signaling, and Wnt/axon guidance pathways.
Milad Ibrahim +4 more
wiley +1 more source

