Topic: unbiased Goto Github
Some thing interesting about unbiased
Some thing interesting about unbiased
unbiased,A dataset bucket with a machine learning bias auditor. Built with Python-Flask, MaterializeCSS and the Kaggle API.
User: kescardoso
Home Page: https://datasetbucket.herokuapp.com
unbiased,Memory efficient seismic inversion via trace estimation
Organization: slimgroup
unbiased,Memory efficient convolution networks
Organization: slimgroup
unbiased,Calculate the mean and standard deviation of a double-precision floating-point strided array.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the mean and standard deviation of a double-precision floating-point strided array using a two-pass algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the mean and variance of a double-precision floating-point strided array.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the mean and variance of a double-precision floating-point strided array using a two-pass algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the standard deviation of a double-precision floating-point strided array ignoring NaN values and using a one-pass algorithm proposed by Youngs and Cramer.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the variance of a double-precision floating-point strided array ignoring NaN values and using a one-pass trial mean algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the variance of a double-precision floating-point strided array ignoring NaN values and using a one-pass textbook algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the variance of a double-precision floating-point strided array ignoring NaN values and using Welford's algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the variance of a double-precision floating-point strided array ignoring NaN values and using a one-pass algorithm proposed by Youngs and Cramer.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the standard deviation of a double-precision floating-point strided array using a one-pass textbook algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the variance of a single-precision floating-point strided array using extended accumulation and returning an extended precision result.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the variance of a double-precision floating-point strided array using a two-pass algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the variance of a double-precision floating-point strided array using a one-pass textbook algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the variance of a double-precision floating-point strided array using Welford's algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the variance of a double-precision floating-point strided array provided a known mean and using Neely's correction algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the standard deviation of a strided array ignoring NaN values and using a one-pass trial mean algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the standard deviation of a strided array ignoring NaN values and using a one-pass textbook algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the standard deviation of a strided array ignoring NaN values and using Welford's algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the variance of a strided array ignoring NaN values and using a one-pass trial mean algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the variance of a strided array ignoring NaN values and using Welford's algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the variance of a strided array ignoring NaN values and using a one-pass algorithm proposed by Youngs and Cramer.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the variance of a single-precision floating-point strided array ignoring NaN values.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the variance of a single-precision floating-point strided array ignoring NaN values and using a one-pass trial mean algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the variance of a single-precision floating-point strided array ignoring NaN values and using a one-pass textbook algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the standard deviation of a single-precision floating-point strided array.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the standard deviation of a single-precision floating-point strided array using a two-pass algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the standard deviation of a single-precision floating-point strided array using a one-pass textbook algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the standard deviation of a strided array.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the standard deviation of a strided array using a two-pass algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the standard deviation of a strided array using Welford's algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the variance of a single-precision floating-point strided array.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the variance of a single-precision floating-point strided array using a two-pass algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the variance of a single-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the variance of a strided array.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the variance of a strided array using a one-pass trial mean algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Calculate the variance of a strided array using a one-pass textbook algorithm.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Compute a sample absolute Pearson product-moment correlation coefficient.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Compute an unbiased sample covariance incrementally.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Compute a moving sample absolute Pearson product-moment correlation coefficient incrementally.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Compute an arithmetic mean and unbiased sample variance incrementally.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Compute a moving unbiased sample variance incrementally.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Compute a moving variance-to-mean ratio (VMR) incrementally.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Compute a sample Pearson product-moment correlation matrix incrementally.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Compute an unbiased sample variance incrementally.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Compute a variance-to-mean ratio (VMR) incrementally.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
unbiased,Compute the unbiased sample variance over all iterated values.
Organization: stdlib-js
Home Page: https://github.com/stdlib-js/stdlib
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