Machine Learning Mastery

1. The regions where the classification scheme fails using linear decision functions are called

  • A Cluster
  • B Indeterminate Region (IR)
  • C Class Boundary
  • D None of These

2.

One clustering algorithm where the density property of the data has been exploited is


  • A Genetic Algorithm
  • B K-Means Algorithm
  • C DBSCAN Algorithm
  • D ID3 Algorithm

3. An example of a Soft clustering algorithm is

  • A Fuzzy C-Means Algorithm
  • B K-Nearest Neighbour Algorithm
  • C CART Algorithm
  • D Naïve Bayes

4.

The decision tree algorithm CART, when applied to Regression problems, attempts to minimise the


  • A Information Gain
  • B Residual Sum of Squares
  • C Gini Index
  • D Intra Cluster Distance

5.

In decision tree-based ML algorithms, the purity of classification in the example data set is measured by


  • A Entropy of the Data set
  • B Information Gain
  • C Residual Sum of Squares
  • D Gini Index

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