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mlr: Machine Learning in R

Bernd Bischl, Michel Lang, Lars Kotthoff, Patrick Schratz et al. (2013)

Interface to a large number of classification and regression techniques, including machine-readable parameter descriptions. There is also an experimental extension for survival analysis, clustering and general, example-specific cost-sensiti...

OPENALEX Open Access DOI: https://doi.org/10.32614/cran.package.mlr

Discovering subtypes with imaging signatures in the Motoric Cognitive Risk Syndrome Consortium using weakly supervised clustering

Bhargav Teja Nallapu, Ali Ezzati, Helena M. Blumen, Kellen K. Petersen et al. • Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring (2025)

ABSTRACT INTRODUCTION Understanding the heterogeneity of brain structure in individuals with the Motoric Cognitive Risk Syndrome (MCR) may improve the current risk assessments of dementia. METHODS We used data from six cohorts from the MCR ...

DOAJ Open Access (DOAJ) DOI: 10.1002/dad2.70197

Surface circulation properties in the eastern Mediterranean emphasized using machine learning methods

G. Baaklini, G. Baaklini, R. El Hourany, M. Fakhri et al. • Ocean Science (2022)

The eastern Mediterranean surface circulation is highly energetic and composed of structures interacting stochastically. However, some main features are still debated, and the behavior of some fine-scale dynamics and their role in shaping t...

DOAJ Open Access (DOAJ) DOI: 10.5194/os-18-1491-2022

Machine Learning in Action

Peter de B. Harrington (2012)

SummaryMachine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. You'll use the flexible Python programming language to bui...

OPENALEX

Taxonomy-based data representation for data mining: an example of the magnitude of risk associated with H. pylori infection

Inese Polaka, Danute Razuka-Ebela, Jin Young Park, Marcis Leja • BioData Mining (2021)

Abstract Background The amount of available and potentially significant data describing study subjects is ever growing with the introduction and integration of different registries and data banks. The single specific attribute of these data...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13040-021-00271-w

Python Machine Learning

Sebastian Raschka (2015)

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analyticsAbout This BookLeverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualizationLearn effect...

OPENALEX

Machine learning in bioinformatics

Pedro Larrañaga, Borja Calvo, Roberto Santana, Concha Bielza et al. • Briefings in Bioinformatics (2006)

This article reviews machine learning methods for bioinformatics. It presents modelling methods, such as supervised classification, clustering and probabilistic graphical models for knowledge discovery, as well as deterministic and stochast...

OPENALEX Open Access DOI: https://doi.org/10.1093/bib/bbk007

Selection of target-binding proteins from the information of weakly enriched phage display libraries by deep sequencing and machine learning

Tomoyuki Ito, Thuy Duong Nguyen, Yutaka Saito, Yoichi Kurumida et al. • mAbs (2023)

Despite the advances in surface-display systems for directed evolution, variants with high affinity are not always enriched due to undesirable biases that increase target-unrelated variants during biopanning. Here, our goal was to design a ...

DOAJ Open Access (DOAJ) DOI: 10.1080/19420862.2023.2168470

Unsupervised machine learning identifies distinct ALS molecular subtypes in post-mortem motor cortex and blood expression data

Heather Marriott, Renata Kabiljo, Guy P Hunt, Ahmad Al Khleifat et al. • Acta Neuropathologica Communications (2023)

Abstract Amyotrophic lateral sclerosis (ALS) displays considerable clinical and genetic heterogeneity. Machine learning approaches have previously been utilised for patient stratification in ALS as they can disentangle complex disease lands...

DOAJ Open Access (DOAJ) DOI: 10.1186/s40478-023-01686-8

A bibliometric analysis of industry 4.0 digital manufacturing and smart technologies for sustainable development

Ferhat Yilmaz, Zeynep Ozguner • Discover Sustainability (2026)

Abstract This study provides a broad bibliometric analysis of Industry 4.0 as well as technology-based production systems within the appropriate scientific literature to target the description of the dynamic structure, intellectual foundati...

DOAJ Open Access (DOAJ) DOI: 10.1007/s43621-026-03275-w

Enhancing Online Security: A Novel Machine Learning Framework for Robust Detection of Known and Unknown Malicious URLs

Shiyun Li, Omar Dib • Journal of Theoretical and Applied Electronic Commerce Research (2024)

The rapid expansion of the internet has led to a corresponding surge in malicious online activities, posing significant threats to users and organizations. Cybercriminals exploit malicious uniform resource locators (URLs) to disseminate har...

DOAJ Open Access (DOAJ) DOI: 10.3390/jtaer19040141