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

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

    Data covering the nonlinear relationships observed in a servo-amplifier circuit. Levels of various components as a function of other components are given. 167 Text Regression 1993 [160] [161] K. Ullrich UJIIndoorLoc-Mag Dataset Indoor localization database to test indoor positioning systems. Data is magnetic field based. Train and test splits ...

  3. TestU01 - Wikipedia

    en.wikipedia.org/wiki/TestU01

    TestU01 is a software library, implemented in the ANSI C language, that offers a collection of utilities for the empirical randomness testing of random number generators (RNGs). [1] The library was first introduced in 2007 by Pierre L’Ecuyer and Richard Simard of the Université de Montréal .

  4. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    The sample size is an important feature of any empirical study in which the goal is to make inferences about a population from a sample. In practice, the sample size used in a study is usually determined based on the cost, time, or convenience of collecting the data, and the need for it to offer sufficient statistical power. In complex studies ...

  5. DHIS2 - Wikipedia

    en.wikipedia.org/wiki/DHIS2

    As a digital solution for data collection and management, DHIS2 can be used for aggregate data (e.g. routine health facility data, staffing, equipment, infrastructure, population estimates, etc.), event data (e.g. disease outbreaks, survey/audit data, patient satisfaction surveys, etc.), and individual-level longitudinal data (e.g. vaccination records, lab sample collection and testing ...

  6. Sampling distribution - Wikipedia

    en.wikipedia.org/wiki/Sampling_distribution

    In statistics, a sampling distribution or finite-sample distribution is the probability distribution of a given random-sample-based statistic.For an arbitrarily large number of samples where each sample, involving multiple observations (data points), is separately used to compute one value of a statistic (for example, the sample mean or sample variance) per sample, the sampling distribution is ...

  7. Determining the number of clusters in a data set - Wikipedia

    en.wikipedia.org/wiki/Determining_the_number_of...

    The average silhouette of the data is another useful criterion for assessing the natural number of clusters. The silhouette of a data instance is a measure of how closely it is matched to data within its cluster and how loosely it is matched to data of the neighboring cluster, i.e., the cluster whose average distance from the datum is lowest. [8]

  8. Walk forward optimization - Wikipedia

    en.wikipedia.org/wiki/Walk_forward_optimization

    In-Sample Data: It is a past segment of market data (historical data) reserved for testing purposes. This data is used for the initial testing and any optimization and is the original parameters of a system under test. Out-of-Sample Data: It is the reserved data set (historical data) which is not a part of the in-sample data. It is important as ...

  9. Resampling (statistics) - Wikipedia

    en.wikipedia.org/wiki/Resampling_(statistics)

    The best example of the plug-in principle, the bootstrapping method. Bootstrapping is a statistical method for estimating the sampling distribution of an estimator by sampling with replacement from the original sample, most often with the purpose of deriving robust estimates of standard errors and confidence intervals of a population parameter like a mean, median, proportion, odds ratio ...