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  2. All supervised machine learning algorithms have an X and a Y. Our “X” set will compromise our independent variables, and a data frame or a matrix will usually represent this. Our “Y” set will have our dependent variable, again as either a data frame or a matrix. Supervised learning means we’re training algorithms using labeled data.
    enjoymachinelearning.com/blog/x-and-y-in-machin…
    X is a matrix of the features values, each column being one feature, and being known values. Each column of X is an independant variable. y is a vector of the target values, being the values you want to try to predict. y has only one column and is the dependant/target variable. A row in X anf y is one data sample.
    datascience.stackexchange.com/questions/105104…
     
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  7. Machine learning of XY model on a spherical …

    WEBSep 1, 2021 · We study the XY model on a spherical surface by using Monte Carlo simulations and machine learning methods. Instead of a traditional latitude-longitude lattice, we consider a much more...

  8. Machine learning of the X Y model on a spherical …

    WEBApr 1, 2022 · The XY model on a spherical surface, inspired by recently realized atomic gases trapped in a spherical shell, is analyzed here. Instead of a traditional latitude-longitude lattice, we introduce...

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