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For clustering of the vs For clustering of the variables

Both phrases are correct, but they are used in different contexts. 'For clustering of the' is used when referring to the action of clustering data points, while 'for clustering of the variables' is used when specifying that variables are being clustered.

Last updated: March 17, 2024 • 560 views

For clustering of the

This phrase is correct and commonly used when referring to the action of clustering data points.

This phrase is used when discussing the process of clustering data points into groups or clusters.

Examples:

  • The algorithm is used for clustering of the data points.
  • For clustering of the images, a specific feature extraction method is employed.
  • In this paper, a new two-level algorithm for clustering of the SOM is proposed. The clustering at the second level is agglomerative hierarchical clustering.
  • First, we used simple toy data for demonstrating the need for clustering of the SOTM. Second, we present applications in two real-world settings: financial ratios  ...
  • compare similarity measures for clustering of the QRS complexes. Distance measures widely used in the time domain. ECG classification algorithms include the ...
  • Feb 14, 2015 ... These dummies give you individual specific intercepts but they do not account for clustering of the errors within individual - and this is what you ...

Alternatives:

  • for clustering the data
  • for performing clustering
  • for data clustering
  • for grouping the data
  • for segmenting the data

For clustering of the variables

This phrase is correct and commonly used when specifying that variables are being clustered.

This phrase is used when discussing the process of clustering variables based on certain criteria or characteristics.

Examples:

  • The method is applied for clustering of the variables in the dataset.
  • For clustering of the variables, a hierarchical clustering approach is utilized.
  • Oct 29, 2014 ... There was little evidence for clustering of the variables within schools, with the interclass correlations for all study vari- ables below .04.

Alternatives:

  • for variable clustering
  • for grouping variables
  • for segmenting variables
  • for categorizing variables
  • for organizing variables

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