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Comparative research is a research methodology in the social sciences exemplified in cross-cultural or comparative studies that aims to make comparisons across different countries or cultures. A major problem in comparative research is that the data sets in different countries may define categories differently (for example by using different ...
Most data files are adapted from UCI Machine Learning Repository data, some are collected from the literature. treated for missing values, numerical attributes only, different percentages of anomalies, labels
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 database of biomedical and life sciences literature with access to full-text research articles and citations. [56] Includes text-mining tools and links to external molecular and medical data sets. A partner in PMC International. [57] Free EMBL-EBI [58] FSTA – Food Science and Technology Abstracts: Food science, food technology, nutrition
Research into the sheepskin effect can be divided into studies of explicit degree effects and, because many of the useful data sets don't explicitly report degrees, studies with no explicit degree measures. The latter typically use 12 years of education as a proxy for a high school diploma and 16 years as a proxy for a Bachelor's degree. [3]
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]
Thus, the input to QCA is a data set of any size, from small-N to large-N, and the output of QCA is a set of descriptive inferences or implications the data supports. In QCA's next step, inferential logic or Boolean algebra is used to simplify or reduce the number of inferences to the minimum set of inferences supported by the data.
Scientific experiments often require comparing two (or more) sets of data. In some cases, the data sets are paired, meaning there is an obvious and meaningful one-to-one correspondence between the data in the first set and the data in the second set, compare Blocking (statistics). For example, paired data can arise from measuring a single set ...