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Large dataset that covers a wider range of reasoning abilities Each task consists of input/output, and a task definition. Additionally, each ask contains a task definition. Further information is provided in the GitHub repository of the project and the Hugging Face data card. Input/Output and task definition 2022 [341] Wang et al. LAMBADA
Caltech-UCSD Birds-200-2011 Dataset Large dataset of images of birds. Part locations for birds, bounding boxes, 312 binary attributes given 11,788 Images, text Classification 2011 [193] [194] C. Wah et al. YouTube-8M Large and diverse labeled video dataset YouTube video IDs and associated labels from a diverse vocabulary of 4800 visual entities
Sports records and statistics (41 C, 30 P) Statistical databases ... Pages in category "Statistical data sets" The following 32 pages are in this category, out of 32 ...
A research question that is asked about big data sets is whether it is necessary to look at the full data to draw certain conclusions about the properties of the data or if is a sample is good enough. The name big data itself contains a term related to size and this is an important characteristic of big data.
Various plots of the multivariate data set Iris flower data set introduced by Ronald Fisher (1936). [1]A data set (or dataset) is a collection of data.In the case of tabular data, a data set corresponds to one or more database tables, where every column of a table represents a particular variable, and each row corresponds to a given record of the data set in question.
In particular, three data sets are commonly used in different stages of the creation of the model: training, validation, and test sets. The model is initially fit on a training data set, [3] which is a set of examples used to fit the parameters (e.g. weights of connections between neurons in artificial neural networks) of the model. [4]
Classic data sets; Classical definition of probability ... Free statistical software; ... Sample (statistics) Sample-continuous process; Sampling (statistics) Simple ...
In the multiple response permutation procedure (MRPP) example above, two datasets with a panel structure are shown and the objective is to test whether there's a significant difference between people in the sample data. Individual characteristics (income, age, sex) are collected for different persons and different years.