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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…
     
  3. People also ask
    How can machine learning be used in a two dimensional lattice?In summary, we have used machine learning methods to study the percolation, the XY model and the GXY model in the two dimensional lattices. For the percola- tion phase transition, the unsupervised t-SNE can map the high dimensional data-sets of configurations into an two-dimensional image with classifiable data.
    Can machine learning be used to study phase transitions?The article has been published as: In this paper, we apply machine learning methods to study phase transitions in certain statistical mechanical models on the two dimensional lattices, whose transitions involve non-local or topological properties, including site and bond percolations, the XY model and the generalized XY model.
    Can machine learning avoid training a network repeatedly?Using previously trained network avoids training the network repeatedly for other system sizes. In summary, we have used machine learning methods to study the percolation, the XY model and the GXY model in the two dimensional lattices.
    What is a spin model in machine learning?Several spin models have recently been studied through machine learning 2, 3, 4, 5, 6. Carrasquilla and Melko 2 proposed a paradigm that is complementary to the above approach. By using large data sets of spin configurations, they classified and identified a high-temperature paramagnetic phase and a low-temperature ferromagnetic phase.
     
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  5. Studies of machine learning xy model
  6. WebFeb 7, 2020 · By studying the 2D clock model, which is a discrete version of the XY model, we classify the paramagnetic-BKT-ferromagnetic

    • Author: Kenta Shiina, Hiroyuki Mori, Yutaka Okabe, Hwee Kuan Lee
    • Publish Year: 2020
  7. WebMay 6, 2019 · Using bare spin configurations as input, the approach is shown to be capable of classifying samples of the two-dimensional XY model by winding number and capture the Berezinskii–Kosterlitz ...

  8. Machine learning of XY model on a spherical Fibonacci lattice

  9. Introduction to the XY Model - Machine Learning | Topological …

  10. Machine learning of XY model on a spherical Fibonacci lattice

  11. Machine learning of phase transitions in the percolation and XY …

  12. Machine learning of phase transitions in the percolation and …

  13. [PDF] Machine learning of phase transitions in the percolation …

  14. Machine learning of XY model on a spherical Fibonacci lattice

  15. Machine learning of phase transitions in the percolation and XY …

  16. Machine learning of XY model on a spherical Fibonacci lattice

  17. Machine learning of XY model on a spherical Fibonacci lattice