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A dataset for NLP and climate change media researchers The dataset is made up of a number of data artifacts (JSON, JSONL & CSV text files & SQLite database) Climate news DB, Project's GitHub repository [395] ADGEfficiency Climatext Climatext is a dataset for sentence-based climate change topic detection. HF dataset [396] University of Zurich ...
Data stored in dataset variables include both raw (as originally collected) and derived values (e.g., converted into standard units, or computed on the basis of multiple values, such as an average). In SDTM only the name, label, and type are listed with a set of CDISC guidelines that provide a general description for each variable used by a ...
Overhead Imagery Research Data Set: Annotated overhead imagery. Images with multiple objects. Over 30 annotations and over 60 statistics that describe the target within the context of the image. 1000 Images, text Classification 2009 [170] [171] F. Tanner et al. SpaceNet SpaceNet is a corpus of commercial satellite imagery and labeled training data.
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
A research design typically outlines the theories and models underlying a project; the research question(s) of a project; a strategy for gathering data and information; and a strategy for producing answers from the data. [1] A strong research design yields valid answers to research questions while weak designs yield unreliable, imprecise or ...
The standards then provide specifications what information about the experiments is crucial and important to be reported together with the resultant data to make it comprehensive. [2] [3] The need for this standardization is largely driven by the development of high-throughput experimental methods that provide tremendous amounts of data. The ...
An industry standard data model, or simply standard data model, is a data model that is widely used in a particular industry. The use of standard data models makes the exchange of information easier and faster because it allows heterogeneous organizations to share an agreed vocabulary, semantics, format, and quality standard for data.
Data standardization - a business rules engine that ensures that data conforms to standards; Geocoding - for name and address data. Corrects data to U.S. and Worldwide geographic standards; Matching or Linking - a way to compare data so that similar, but slightly different records can be aligned. Matching may use "fuzzy logic" to find ...