Kernel Trick MCQ

Test your knowledge with important Kernel Trick MCQ and their applications. These MCQs are beneficial for competitive exams too. Explore 30 + more Kernel Trick MCQs at Bissoy

• Which of the following statements is not true about choosing the right kernel?
  ক

  Linear kernel allows to picking out hyper spheres

  খ

  A polynomial kernel allows to model feature conjunctions up to the order of the polynomial

  গ

  Radial basis functions allow to pick out circles

  ঘ

  Linear kernel allows picking out lines
• Which of the following statements is not true about kernel properties?
  ক

  Kernel functions must be continuous

  খ

  Kernel functions must be symmetric

  গ

  Kernels which are said to satisfy the Mercer’s theorem are negative semi-definite

  ঘ

  Kernel functions most preferably should have a positive (semi-) definite Gram matrix
• Spectrum Kernel count the number of substrings in common.
  ক

  True

  খ

  False
• The Gaussian kernel is also called the RBF kernel, for Radial Basis Functions.
  ক

  True

  খ

  False
• Which of the following statements is not true about kernel trick?
  ক

  It allows one to incorporate prior knowledge of the problem domain

  খ

  The training data only enter the algorithm through their entries in the kernel matrix

  গ

  The training data only enter the algorithm through their individual attributes

  ঘ

  The number of operations required is not necessarily proportional to the number of features
• The k degree polynomial kernel is defined as K(x, x’) = (1 + <x, x’>)k.
  ক

  True

  খ

  False
• A Hilbert space is a vector space with an inner product, which is also complete.
  ক

  True

  খ

  False
• Which of the following statements is not true about the learning algorithms?
  ক

  A feature mapping can be viewed as expanding the class of linear classifiers to a richer class

  খ

  The suitability of any hypothesis class to a given learning task depends on the nature of that task

  গ

  An embedding is a way to express and utilise prior knowledge about the problem at hand

  ঘ

  The sample complexity required to learn with some kinds of kernels is independent of the margin in the feature space
• Many learning algorithms for half-spaces can be carried out just on the basis of the values of the kernel function over pairs of domain points.
  ক

  True

  খ

  False
• Which of the following statements is not true about kernel?
  ক

  Kernel is used to describe inner products in the feature space

  খ

  The kernel function K specify the similarity between instances

  গ

  The kernel function K specify the embedding as mapping the domain set into a space

  ঘ

  The kernel function does the mapping of the domain set into a space where the similarities are realised as outer products
• When we make the half-space learning more expressive, the computational complexity of learning may increase.
  ক

  False

  খ

  True