AI tool predicts how DNA sequences switch on genes across different cell types

Deep learning approaches have transformed how scientists predict the activity and function of DNA sequences in the genome. A ...
Scientific Research Publishing

Performance Analysis of Support Vector Machine (SVM) on Challenging Datasets for Forest Fire Detection ()

1 Department of Computer Science, Chennai Mathematical Institute, Chennai, India. 2 Department of Mathematics & Computer Science, Chennai Mathematical Institute, Chennai, India. 3 Department of Data ...
IEEE

Privacy-Preserving Classification Scheme Based on Support Vector Machine

Abstract: As a classifier, support vector machine (SVM) explains a core problem of machine learning, namely sample classification in statistical terms. It has been widely used in machine learning, ...
Frontiers

Applications of Support Vector Machine in Genomic Prediction in Pig and Maize Populations

Genomic prediction (GP) has revolutionized animal and plant breeding. However, better statistical models that can improve the accuracy of GP are required. For this reason, in this study, we explored ...
Frontiers

PSBP-SVM: A Machine Learning-Based Computational Identifier for Predicting Polystyrene Binding Peptides

Polystyrene binding peptides (PSBPs) play a key role in the immobilization process. The correct identification of PSBPs is the first step of all related works. In this paper, we proposed a novel ...
Nature

Machine learning: supervised methods

In supervised learning, a set of input variables, such as blood metabolite or gene expression levels, are used to predict a quantitative response variable like hormone level or a qualitative one such ...
C&EN

Support Vector Machine Classification and Regression Prioritize Different Structural Features for Binary Compound Activity and Potency Value Prediction

In computational chemistry and chemoinformatics, the support vector machine (SVM) algorithm is among the most widely used machine learning methods for the identification of new active compounds. In ...
IEEE

Generalized SMO Algorithm for SVM-Based Multitask Learning

Abstract: Exploiting additional information to improve traditional inductive learning is an active research area in machine learning. In many supervised-learning applications, training data can be ...