Distance Metrics and Data Transformation
نویسنده
چکیده
2 Distance metrics and similarity measures 2 2.1 Distance metrics . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.2 Vector norm and metric . . . . . . . . . . . . . . . . . . . . . . . 3 2.3 The `p norm and `p metric . . . . . . . . . . . . . . . . . . . . . 3 2.4 Distance metric learning . . . . . . . . . . . . . . . . . . . . . . . 6 2.5 The mean as a similarity measure . . . . . . . . . . . . . . . . . . 7 2.6 Power mean kernel . . . . . . . . . . . . . . . . . . . . . . . . . . 8
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An important class of Finsler metric is named Kropina metrics which is defined by Riemannian metric α and 1-form β which have many applications in physic, magnetic field and dynamic systems. In this paper, conformal transformations of χ-curvature and H-curvature of Kropina metrics are studied and the conditions that preserve this quantities are investigated. Also it is shown that in the ...
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