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  2. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Major advances in this field can result from advances in learning algorithms (such as deep learning), computer hardware, and, less-intuitively, the availability of high-quality training datasets. [1] High-quality labeled training datasets for supervised and semi-supervised machine learning algorithms are usually difficult and expensive to ...

  3. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    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]

  4. MNIST database - Wikipedia

    en.wikipedia.org/wiki/MNIST_database

    The set of images in the MNIST database was created in 1994. Previously, NIST released two datasets: Special Database 1 (NIST Test Data I, or SD-1); and Special Database 3 (or SD-2). They were released on two CD-ROMs. SD-1 was the test set, and it contained digits written by high school students, 58,646 images written by 500 different writers.

  5. Longitudinal study - Wikipedia

    en.wikipedia.org/wiki/Longitudinal_study

    A longitudinal study (or longitudinal survey, or panel study) is a research design that involves repeated observations of the same variables (e.g., people) over long periods of time (i.e., uses longitudinal data). It is often a type of observational study, although it can also be structured as longitudinal randomized experiment. [1]

  6. Multilevel modeling for repeated measures - Wikipedia

    en.wikipedia.org/wiki/Multilevel_Modeling_for...

    One application of multilevel modeling (MLM) is the analysis of repeated measures data. Multilevel modeling for repeated measures data is most often discussed in the context of modeling change over time (i.e. growth curve modeling for longitudinal designs); however, it may also be used for repeated measures data in which time is not a factor.

  7. The Pile (dataset) - Wikipedia

    en.wikipedia.org/wiki/The_Pile_(dataset)

    The Pile is an 886.03 GB diverse, open-source dataset of English text created as a training dataset for large language models (LLMs). It was constructed by EleutherAI in 2020 and publicly released on December 31 of that year. [1] [2] It is composed of 22 smaller datasets, including 14 new ones. [1]

  8. High School and Beyond - Wikipedia

    en.wikipedia.org/wiki/High_School_and_Beyond

    High School and Beyond (HS&B) is a longitudinal study of a nationally representative sample of people who were high school sophomores and seniors in 1980. The study was originally funded by the United States Department of Education ’s National Center for Education Statistics (NCES) as a part of their Secondary Longitudinal Studies Program .

  9. National Longitudinal Study of Adolescent to Adult Health

    en.wikipedia.org/wiki/National_Longitudinal...

    The National Longitudinal Study of Adolescent to Adult Health, also known as Add Health, is a multiwave longitudinal study of adolescents in the United States. It was begun in 1994 in response to a Congressional mandate to study adolescent health , and was initially called the National Longitudinal Study of Adolescent Health . [ 1 ]