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Data from: Automatic recognition of self-acknowledged limitations in clinical research literature
- 负责人:
- DOI:
- doi:10.5061/dryad.06ds7
- 摘要:
- the training set in order to improve classification performance. The machine learning algorithms used were logistic regression (LR) and support vector machines
Data from: A systems toxicology approach for the prediction of kidney toxicity and its mechanisms in vitro
- 负责人:
- DOI:
- doi:10.5061/dryad.646v2r1
- 摘要:
- . Here, we used primary human kidney cells and applied a systems biology approach that combines multidimensional datasets and machine learning to identify
Data from: Impact of ecological redundancy on the performance of machine learning classifiers in vegetation mapping
- 负责人:
- DOI:
- doi:10.5061/dryad.1m8tg17
- 摘要:
- relationship) to evaluate the performance of four machine learning (ML) classifiers (classification trees, random forests, support vector machines
Data from: Mie scattering and microparticle based characterization of heavy metal ions and classification by statistical inference methods
- 负责人:
- DOI:
- doi:10.5061/dryad.62n8p0q
- 摘要:
- and aggregated particles. Classification of these observations was conducted and compared among several machine learning techniques, including
Data from: Automatic supporting system for regionalization of ventricular tachycardia exit site in implantable defibrillators
- 负责人:
- DOI:
- doi:10.5061/dryad.nm0v0
- 摘要:
- ng the anatomical location of the Left Ventricular Tachycardia exit site (LVTES). Our aim here was to evaluate the possibilities from a machine learning
Data from: Machine learning-based differential network analysis: a study of stress-responsive transcriptomes in Arabidopsis thaliana
- 负责人:
- DOI:
- doi:10.5061/dryad.41b9g
- 摘要:
- Machine learning (ML) is an intelligent data mining technique that builds a prediction model based on the learning of prior knowledge to recogni
Data from: Development of machine learning models for diagnosis of glaucoma
- 负责人:
- DOI:
- doi:10.5061/dryad.q6ft5
- 摘要:
- The study aimed to develop machine learning models that have strong prediction power and interpretability for diagnosis of glaucoma based
Data from: I meant to do that: determining the intentions of action in the face of disturbances
- 负责人:
- DOI:
- doi:10.5061/dryad.1257p
- 摘要:
- the target. Knowing such an intent signal is broadly applicable: enhanced human-machine interaction, the study of impaired intent in neural disorders, the rea
Data from: Integrating life history traits into predictive phylogeography
- 负责人:
- DOI:
- doi:10.5061/dryad.s6v210k
- 摘要:
- about unsampled taxa using machine-learning techniques such as Random Forests. To date, organismal trait data have infrequently been incorporated into predictive
Data from: Biogeographic and anthropogenic correlates of Aleutian Islands plant diversity: a machine-learning approach
- 负责人:
- DOI:
- doi:10.5061/dryad.r12cq4r
- 摘要:
- ng machine learning, stochastic boosting- TreeNet,) based on classic and Aleutians-specific island biogeography hypotheses. Plant species richness is strongl