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- In machine learning, the X and Y sets are used in supervised learning algorithms1. X is a matrix of the features values, each column being one feature, and being known values. Each column of X is an independent 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 dependent/target variable. A row in X and Y is one data sample2.
Learn more:✕This summary was generated using AI based on multiple online sources. To view the original source information, use the "Learn more" links.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… - People also ask
Machine learning of XY model on a spherical Fibonacci lattice
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Machine learning of XY model on a spherical Fibonacci lattice
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Physical Review Link Manager
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Machine learning of XY model on a spherical Fibonacci lattice
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