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Results for multiple kernel function

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14 papers · ranked by Valyu relevance

01
PPubMed13 Apr 2022
Weighted <i> p </i> -norm distance t kernel SVM classification algorithm based on improved polarization
Wenbo Liu, Shengnan Liang, Xiwen Qin
The kernel function in SVM enables linear segmentation in a feature space for a large number of linear inseparable data. The kernel function that is selected directly affects the classification performance of SVM. To improve the applicability and classification prediction effect of SVM in different areas, in this…
83relevance
02
PPubMed2 Feb 2024
Study of PARP inhibitors for breast cancer based on enhanced multiple kernel function SVR with PSO Xue et al. 10.3389/fphar.2024.1257253
Haohan Xue, Ruixuan Zhang, Xudong Yan, Ruihan Wang + 1 more
PARP1 is one of six enzymes required for the highly error-prone DNA repair pathway microhomology-mediated end joining (MMEJ) and needs to be inhibited when over-expressed. In order to study the PARP1 inhibitory effect of fused tetracyclic or pentacyclic dihydrodiazepinoindolone derivatives (FTPDDs) by quantitative…
81relevance
03
PPubMed23 Nov 2024
Supervised multiple kernel learning approaches for multi-omics data integration
Mitja Briscik, Gabriele Tazza, László Vidács, Marie-Agnès Dillies + 1 more
'Sébastien Déjean'] Background Advances in high-throughput technologies have originated an ever-increasing availability of omics datasets. The integration of multiple heterogeneous data sources is currently an issue for biology and bioinformatics. Multiple kernel learning (MKL) has shown to be a flexible and valid…
81relevance
04
PPubMed8 Nov 2022
Feature-space selection with banded ridge regression
Tom Dupré la Tour, Michael Eickenberg, Anwar O. Nunez-Elizalde, Jack L. Gallant
'Jack L. Gallant'] Encoding models provide a powerful framework to identify the information represented in brain recordings. In this framework, a stimulus representation is expressed within a feature space and is used in a regularized linear regression to predict brain activity. To account for a potential…
75relevance
05
PPubMed13 Feb 2025
Cost-sensitive multi-kernel ELM based on reduced expectation kernel auto-encoder Cost-sensitive Multi-kernel ELM
Liang Yixuan, Longhui Qin
ELM (Extreme learning machine) has drawn great attention due its high training speed and outstanding generalization performance. To solve the problem that the long training time of kernel ELM auto-encoder and the difficult setting of the weight of kernel function in the existing multi-kernel models, a multi-kernel…
73relevance
06
PPubMed5 Feb 2023
Reservoir Lithology Identification Based on Multicore Ensemble Learning and Multiclassification Algorithm Based on Noise Detection Function
Menglei Li, Chaomo Zhang, Iván García-Magariño, Shah Nazir + 1 more
'Habib Ullah Khan'] Reservoir lithology identification is an important part of well logging interpretation. The accuracy of identification affects the subsequent exploration and development work, such as reservoir division and reserve prediction. Correct reservoir lithology identification has important geological…
71relevance
07
PPubMed28 Jan 2022
Multivariate Functional Kernel Machine Regression and Sparse Functional Feature Selection
Joseph Naiman, Peter Xuekun Song, S. Ejaz Ahmed, Farouk Nathoo
Motivated by mobile devices that record data at a high frequency, we propose a new methodological framework for analyzing a semi-parametric regression model that allow us to study a nonlinear relationship between a scalar response and multiple functional predictors in the presence of scalar covariates. Utilizing…
69relevance
08
CchemRxiv28 Aug 2025
An Adapted Similarity Kernel and Generalised Convex Hull for Molecular Crystal Structure Prediction
Authors not listed
We adapted an existing approach to identifying stabilisable crystal structures from prediction sets - the Generalised Convex Hull (GCH) - to improve its application to molecular crystal structures. This was achieved by modifying the Smooth Overlap of Atomic Positions (SOAP) kernel to define the similarity of molecular…
63relevance
09
CchemRxiv28 Dec 2025
Accurate and Robust Analysis of Molecular Kinetics with Random Features
Authors not listed
Metastable states and the conformational transitions in between them are key to understanding dynamical behaviour and function of large-scale molecular systems. By combining basic dimensionality reduction techniques with a state-of-the art approximation of the Koopman operator associated to molecular dynamics…
63relevance
10
CchemRxiv8 Mar 2022
Classifying the toxicity of pesticides to honey bees via support vector machines with random walk graph kernels
Ping Yang, E. Adrian Henle, Cory M. Simon, Xiaoli Fern
Pesticides benefit agriculture by increasing crop yield, quality, and security. However, pesticides may inadvertently harm bees, which are valuable as pollinators. Thus, candidate pesticides in development pipelines must be assessed for toxicity to bees. Leveraging a data set of 382 molecules with toxicity labels from…
62relevance
11
CchemRxiv10 Mar 2022
Classifying the toxicity of pesticides to honey bees via support vector machines with random walk graph kernels
Ping Yang, E. Adrian Henle, Xiaoli Fern, Cory M. Simon
Pesticides benefit agriculture by increasing crop yield, quality, and security. However, pesticides may inadvertently harm bees, which are agriculturally and ecologically vital as pollinators. The development of new pesticides---driven by pest resistance to and demands to reduce negative environmental impacts of…
59relevance
12
CchemRxiv21 Sep 2023
Machine Learning of Reactive Potentials
Yinuo Yang, Shuhao Zhang, Kavindri Ranasinghe, Olexandr Isayev + 1 more
In the past two decades, machine learning potentials (MLPs) have driven significant developments in chemical, biological and material sciences. The construction and training of MLPs enables fast and accurate simulations and analysis on thermodynamic and kinetic properties. This review focuses on the applications of…
56relevance
13
CchemRxiv25 Mar 2024
Beyond Molecular Structure: Critically Assessing Machine Learning for Designing Organic Photovoltaic Materials and Devices
Martin Seifrid, Stanley Lo, Dylan Choi, Gary Tom + 12 more
Martin Seifrid 1 , Stanley Lo 2 , Dylan G. Choi 3 , Gary Tom 2 , My Linh Le 3 , Kunyu Li 3 , Rahul Sankar 3 , Hoai-Thanh Vuong 3 , Hiba Wakidi 3 , Ahra Yi 3 , Ziyue Zhu 3 , Nora Schopp 3 , Aaron Peng 3 , Benjamin Luginbuhl 3 , Thuc-Quyen Nguyen 3 , Alán Aspuru-Guzik 2
56relevance
14
CchemRxiv15 Jun 2022
Krein Support Vector Machine Classification of Antimicrobial Peptides
Joseph Redshaw, Darren Ting, Alex Brown, Jonathan Hirst + 1 more
Antimicrobial peptides (AMPs) represent a potential solution to the growing problem of antimicrobial resistance, yet their identification through wet-lab experiments is a costly and timeconsuming process. Accurate computational predictions would allow rapid in silico screening of candidate AMPs, thereby accelerating…
56relevance

Results for multiple kernel function

Weighted <i> p </i> -norm distance t kernel SVM classification algorithm based on improved polarization

Study of PARP inhibitors for breast cancer based on enhanced multiple kernel function SVR with PSO Xue et al. 10.3389/fphar.2024.1257253

Supervised multiple kernel learning approaches for multi-omics data integration

Feature-space selection with banded ridge regression

Cost-sensitive multi-kernel ELM based on reduced expectation kernel auto-encoder Cost-sensitive Multi-kernel ELM

Reservoir Lithology Identification Based on Multicore Ensemble Learning and Multiclassification Algorithm Based on Noise Detection Function

Multivariate Functional Kernel Machine Regression and Sparse Functional Feature Selection

An Adapted Similarity Kernel and Generalised Convex Hull for Molecular Crystal Structure Prediction

Accurate and Robust Analysis of Molecular Kinetics with Random Features

Classifying the toxicity of pesticides to honey bees via support vector machines with random walk graph kernels

Classifying the toxicity of pesticides to honey bees via support vector machines with random walk graph kernels

Machine Learning of Reactive Potentials

Beyond Molecular Structure: Critically Assessing Machine Learning for Designing Organic Photovoltaic Materials and Devices

Krein Support Vector Machine Classification of Antimicrobial Peptides

Weighted <i> p </i> -norm distance t kernel SVM classification algorithm based on improved polarization

Study of PARP inhibitors for breast cancer based on enhanced multiple kernel function SVR with PSO Xue et al. 10.3389/fphar.2024.1257253

Supervised multiple kernel learning approaches for multi-omics data integration

Feature-space selection with banded ridge regression

Cost-sensitive multi-kernel ELM based on reduced expectation kernel auto-encoder Cost-sensitive Multi-kernel ELM

Reservoir Lithology Identification Based on Multicore Ensemble Learning and Multiclassification Algorithm Based on Noise Detection Function

Multivariate Functional Kernel Machine Regression and Sparse Functional Feature Selection

An Adapted Similarity Kernel and Generalised Convex Hull for Molecular Crystal Structure Prediction

Accurate and Robust Analysis of Molecular Kinetics with Random Features

Classifying the toxicity of pesticides to honey bees via support vector machines with random walk graph kernels

Classifying the toxicity of pesticides to honey bees via support vector machines with random walk graph kernels

Machine Learning of Reactive Potentials

Beyond Molecular Structure: Critically Assessing Machine Learning for Designing Organic Photovoltaic Materials and Devices

Krein Support Vector Machine Classification of Antimicrobial Peptides