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==메타데이터==
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===위키데이터===
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* ID :  [https://www.wikidata.org/wiki/Q44528 Q44528]
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===Spacy 패턴 목록===
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* [{'LOWER': 'euclidean'}, {'LEMMA': 'vector'}]
 +
* [{'LOWER': 'geometric'}, {'LEMMA': 'vector'}]
 +
* [{'LOWER': 'spatial'}, {'LEMMA': 'vector'}]
 +
* [{'LEMMA': 'vector'}]

2021년 2월 17일 (수) 01:07 기준 최신판

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위키데이터

말뭉치

  1. So how do we rotate the row vector?[1]
  2. The general vector space does not have a multiplication which multiples two vectors to give a third.[1]
  3. To illustrate the issue: imagine a vector P1 which happens to be (4,5).[1]
  4. Suppose a vector of lower dimension also exists in the higher dimensional space.[2]
  5. You can then set all of the missing components in the lower dimensional vector to 0 so that both vectors have the same dimension.[2]
  6. It is calculated using some measure that summarizes the distance of the vector from the origin of the vector space.[3]
  7. The L1 norm is calculated as the sum of the absolute vector values, where the absolute value of a scalar uses the notation |a1|.[3]
  8. Max norm of a vector is referred to as L^inf where inf is a superscript and can be represented with the infinity symbol.[3]
  9. Geometrically, the distance between the points is equal to the magnitude of the vector that extends from one point to the other.[4]
  10. A row vector with n component will be called an n-vector.[5]
  11. The mathematical representation of a physical vector depends on the coordinate system used to describe it.[6]
  12. Other vector-like objects that describe physical quantities and transform in a similar way under changes of the coordinate system include pseudovectors and tensors.[6]
  13. In the programmer’s perspective, there are many situation where you need to compute different vector operations.[7]
  14. Now in this article, I will show you how to compute different vector operations like sum of two vectors, multiplication by scalar, dot product, cross product, normalization etc in C++.[7]
  15. The vector can be represented by an object.[7]
  16. The components of vector along x, y and z-axis will be the data member of the object.[7]
  17. For mathematical vectors in general, see Vector (mathematics and physics).[8]
  18. A vector is a geometric entity characterized by a magnitude (in mathematics a number, in physics a number times a unit) and a direction.[8]
  19. a vector is defined as a directed line segment, or arrow, in a Euclidean space.[8]
  20. As an arrow in Euclidean space, a vector possesses a definite initial point and terminal point.[8]
  21. Vectors can be added to other vectors according to vector algebra.[9]
  22. These operations and associated laws qualify Euclidean vectors as an example of the more generalized concept of vectors defined simply as elements of a vector space.[9]
  23. The position of the particle P j is exactly determined by a vector r j ∈ R3 from O spatial to the location of P j .[10]
  24. The word vector comes from Latin, where it means "carrier.[11]
  25. Dot Product You may have noticed that while we did define multiplication of a vector by a scalar in the previous section on vector algebra, we did not define multiplication of a vector by a vector.[11]
  26. The resulting product, however, was a scalar, not a vector.[11]
  27. In this section we will define a product of two vectors that does result in another vector.[11]
  28. A Euclidean vector is frequently represented by a line segment with a definite direction, or graphically as an arrow, connecting an initial point A with a terminal point B, and denoted by A B → .[12]
  29. In mathematics, physics, and engineering, a Euclidean vector is a geometric object that has magnitude and direction and can be added to other vectors according to vector algebra.[13]
  30. It is important to distinguish Euclidean vectors from the more general concept in linear algebra of vectors as elements of a vector space.[13]
  31. In turn, both of these definitions of vector should be distinguished from the statistical concept of a random vector.[13]
  32. Here we have a column vector in ℝ², which is an abstract arrow emanating from Origin (0, 0) and pointing towards the point (x, y).[14]
  33. Each of the numbers in this vector is called a component.[14]
  34. When we talk about multiplying the vector by a number, often, we call them scalars.[14]
  35. If we use a scalar to multiple the vector, the result equals to we multiple every component with this scalar.[14]
  36. In ℝ n , a vector can be easily constructed as the line segment between points whose in each coordinate are the components of the vector.[15]
  37. A vector constructed at the origin (The vector ( 3 , 4 ) drawn from the point ( 0 , 0 ) to ( 3 , 4 ) ) is called a position vector.[15]
  38. Note that a vector that is not a position vector is of position.[15]
  39. The magnitude of the vector comes from the metric of the space it is embedded in.[15]
  40. Another definition of Euclidean spaces by means of vector spaces and linear algebra has been shown to be equivalent to the axiomatic definition.[16]
  41. The introduction of abstract vector spaces allowed their use in defining Euclidean spaces with a purely algebraic definition.[16]
  42. If E is a Euclidean space, its associated vector space is often denoted E → .[16]
  43. (The second + in the left-hand side is a vector addition; all other + denote an action of a vector on a point.[16]
  44. For mathematical vectors in general, see Vector (mathematics and physics) .[17]
  45. + v of a Real number s (also called scalar) and a 3-dimensional vector.[17]
  46. In physics and engineering, a vector is typically regarded as a geometric entity characterized by a magnitude and a direction.[17]
  47. In pure mathematics, a vector is defined more generally as any element of a vector space.[17]
  48. A vector becomes a triple of real numbers, its components.[18]
  49. One has to keep in mind, however, that the components of a physical vector depend on the coordinate system used to describe it.[18]
  50. Informally, a vector is a quantity characterized by a magnitude (in mathematics a number, in physics a number times a unit) and a direction, often represented graphically by an arrow.[18]
  51. For example, the velocity 5 meters per second upward could be represented by the vector (0,5).[18]

소스

  1. ↑ 1.0 1.1 1.2 Vector Space and Bases
  2. ↑ 2.0 2.1 Calculate distance between two vectors of different length
  3. ↑ 3.0 3.1 3.2 Gentle Introduction to Vector Norms in Machine Learning
  4. ↑ Vector and matrix norms
  5. ↑ Linear Algebra Webnotes. Part 4.
  6. ↑ 6.0 6.1 Euclidean Vector Space
  7. ↑ 7.0 7.1 7.2 7.3 Basic Euclidean vector operations in C++
  8. ↑ 8.0 8.1 8.2 8.3 Euclidean vector
  9. ↑ 9.0 9.1 About: Euclidean vector
  10. ↑ Euclidean Inner Product - an overview
  11. ↑ 11.0 11.1 11.2 11.3 1: Vectors in Euclidean Space
  12. ↑ Euclidean vector
  13. ↑ 13.0 13.1 13.2 What does euclidean vector mean?
  14. ↑ 14.0 14.1 14.2 14.3 Linear Algebra 1 | Euclidean Space, Vectors, and Dot Product
  15. ↑ 15.0 15.1 15.2 15.3 Euclidean vector
  16. ↑ 16.0 16.1 16.2 16.3 Euclidean space
  17. ↑ 17.0 17.1 17.2 17.3 Euclidean vector
  18. ↑ 18.0 18.1 18.2 18.3 Euclidean vector

메타데이터

위키데이터

Spacy 패턴 목록

  • [{'LOWER': 'euclidean'}, {'LEMMA': 'vector'}]
  • [{'LOWER': 'geometric'}, {'LEMMA': 'vector'}]
  • [{'LOWER': 'spatial'}, {'LEMMA': 'vector'}]
  • [{'LEMMA': 'vector'}]
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