Sentence examples for datasets were classified using from inspiring English sources
For effective characterization of soil moisture variation, soil moisture datasets were classified using cluster analysis based on Euclidean similarity.
Both MBC datasets were classified using these ER+ FBC luminal centroids.
These datasets were classified using BioHEL and other machine learning methods, as the canine proteomic dataset was, reported in a recent paper by Swan et al., [ 25].
Secondly, pathway-based functional orthology of the dataset was classified using the KEGG (Kyoto Encyclopedia of Genes and Genomes) Automated Annotation Server (KAAS) [ 100].
Hydrologic regimes were classified using a shape-magnitude framework and seven wetland classes were characterized, and the robustness of this classification is assessed using longer-term datasets.
Similarly to datasets, all WINGS components are classified using an ontology where an individual component can either be classified as its own entity or grouped under a super-component class termed "component-type".
These BDAs comprised the training dataset, leaving the remaining 34,972 BDAs to be classified using model results.
Ethnicity was classified using the most recent valid self-assigned ethnicity code from the Hospital Episode Statistics (HES) dataset.
Subjects in this dataset were classified as CFS using the CDC Symptom Inventory, Multidimensional Fatigue Inventory (MFI) and Short Form 36 (SF-36) instruments [ 17, 18].
