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Хамит Хан

Khamit Zhussip 17 questions

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Questions in this quiz (17)

  1. 1Another name for an output attribute.
    1. Adependent variable
    2. Bpredictive variable
    3. Cindependent variable
    4. Destimated variable
  2. 2A multiple regression model has
    1. Amore than one independent variable
    2. Bonly one independent variable
    3. Cmore than one dependent variable
    4. Dnone of the above
  3. 3Which of the following is characteristic of Processed Data ?
    1. AAll steps should be noted
    2. BData is not ready for analysis
    3. CHard to use for data analysis
    4. DNone of the mentioned
  4. 4Point out the correct statement:
    1. AAll of the Mentioned
    2. BThe choice of an appropriate metric will influence the shape of the clusters
    3. CHierarchical clustering is also called HCA
    4. DIn general, the merges and splits are determined in a greedy manner
  5. 5This technique associates a conditional probability value with each data instance.
    1. Alogistic regression
    2. Blinear regression
    3. Csimple regression
    4. Dmultiple linear regression
  6. 6A regression model in which more than one independent variable is used to predict the dependent variable is called
    1. Aa multiple regression models
    2. Ba simple linear regression model
    3. Can independent model
    4. Dnone of the above
  7. 7Supervised learning and unsupervised clustering both require at least one
    1. Ainput attribute.
    2. Bhidden attribute.
    3. Coutput attribute.
    4. Dcategorical attribute.
  8. 8Selecting data so as to assure that each class is properly represented in both the training and test set.
    1. Astratification
    2. Bcross validation
    3. Cverification
    4. Dbootstrapping
  9. 9Which statement is true about prediction problems?
    1. AThe resultant model is designed to determine future outcomes.
    2. BThe output attribute must be categorical.
    3. CThe output attribute must be numeric.
    4. DThe resultant model is designed to classify current behavior.
  10. 10Bootstrapping allows us to
    1. Achoose the same training instance several times.
    2. Bchoose the same test set instance several times.
    3. Cbuild models with alternative subsets of the training data several times.
    4. Dtest a model with alternative subsets of the test data several times.

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Quiz on Хамит Хан, created by Khamit Zhussip on 19/12/2018.
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