Prediction is

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Question:
Prediction is

1. the result of application of specific theory or rule in a specific case

2.discipline in statistics used to find projections in multidimensional data

3.value entered in database by expert

4.independent of data

Posted Date:-2022-06-21 03:35:05

More MCQS Questions and answers

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  2. If machine learning model output doesnot involves target variable then that model is called as
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  4. In multiclass classification number of classes must be
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  7. A feature F1 can take certain value: A, B, C, D, E, & F and represents grade of students from a college. Here feature type is
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  9. A person trained to interact with a human expert in order to capture their knowledge.
  10. A student Grade is a variable F1 which takes a value from A,B,C and D. Which of the following is True in the following case?
  11. Application of machine learning methods to large databases is called
  12. Data used to build a data mining model.
  13. Different learning methods does not include?
  14. Feature can be used as a
  15. Following are the descriptive models
  16. Following are the types of supervised learning
  17. If machine learning model output involves target variable then that model is called as
  18. Imagine a Newly-Born starts to learn walking. It will try to find a suitable policy to learn walking after repeated falling and getting up.specify what type of machine learning is best suited?
  19. Impact of high variance on the training set ?
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  22. Like the probabilistic view, the ________ view allows us to associate a probability of membership with each classification.
  23. Of the Following Examples, Which would you address using an supervised learning Algorithm?
  24. ollowing is powerful distance metrics used by Geometric model
  25. PCA is
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  28. Some telecommunication company wants to segment their customers into distinct groups ,this is an example of
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  30. Support Vector Machine is
  31. The "curse of dimensionality" referes
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  34. The output of training process in machine learning is
  35. The problem of finding hidden structure in unlabeled data is called…
  36. Type of matrix decomposition model is
  37. What can be major issue in Leave-One-Out-Cross-Validation(LOOCV)?
  38. What characterize is hyperplance in geometrical model of machine learning?
  39. What characterize unlabeled examples in machine learning
  40. What do you mean by a hard margin?
  41. What does dimensionality reduction reduce?
  42. Which learning Requires Self Assessment to identify patterns within data?
  43. Which of the folllowing is an example of feature extraction?
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  45. Which of the following is a good test dataset characteristic?
  46. Which of the following is a reasonable way to select the number of principal components "k"?
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