Difference between revisions of "Orange: Correlations"

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(Created page with "Sumber: https://docs.biolab.si//3/visual-programming/widgets/data/correlations.html Compute all pairwise attribute correlations. Inputs Data: input dataset Outputs...")
 
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Correlations computes Pearson or Spearman correlation scores for all pairs of features in a dataset. These methods can only detect monotonic relationship.
 
Correlations computes Pearson or Spearman correlation scores for all pairs of features in a dataset. These methods can only detect monotonic relationship.
  
../../_images/Correlations-stamped.png
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[[File:Correlations-stamped.png|center|200px|thumb]]
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     Correlation measure:
 
     Correlation measure:
  
 
         Pairwise Pearson correlation.
 
         Pairwise Pearson correlation.
 
 
         Pairwise Spearman correlation.
 
         Pairwise Spearman correlation.
  
 
     Filter for finding attribute pairs.
 
     Filter for finding attribute pairs.
 
 
     A list of attribute pairs with correlation coefficient. Press Finished to stop computation for large datasets.
 
     A list of attribute pairs with correlation coefficient. Press Finished to stop computation for large datasets.
 
 
     Access widget help and produce report.
 
     Access widget help and produce report.
  
Example
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==Contoh==
  
 
Correlations can be computed only for numeric (continuous) features, so we will use housing as an example data set. Load it in the File widget and connect it to Correlations. Positively correlated feature pairs will be at the top of the list and negatively correlated will be at the bottom.
 
Correlations can be computed only for numeric (continuous) features, so we will use housing as an example data set. Load it in the File widget and connect it to Correlations. Positively correlated feature pairs will be at the top of the list and negatively correlated will be at the bottom.
  
../../_images/Correlations-links.png
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[[File:Correlations-links.png|center|200px|thumb]]
 +
 
  
 
Go to the most negatively correlated pair, DIS-NOX. Now connect Scatter Plot to Correlations and set two outputs, Data to Data and Features to Features. Observe how the feature pair is immediately set in the scatter plot. Looks like the two features are indeed negatively correlated.
 
Go to the most negatively correlated pair, DIS-NOX. Now connect Scatter Plot to Correlations and set two outputs, Data to Data and Features to Features. Observe how the feature pair is immediately set in the scatter plot. Looks like the two features are indeed negatively correlated.
  
../../_images/Correlations-Example.png
+
[[File:Correlations-Example.png|center|200px|thumb]]
 
 
  
  

Revision as of 10:00, 22 January 2020

Sumber: https://docs.biolab.si//3/visual-programming/widgets/data/correlations.html


Compute all pairwise attribute correlations.

Inputs

   Data: input dataset

Outputs

   Data: input dataset
   Features: selected pair of features
   Correlations: data table with correlation scores

Correlations computes Pearson or Spearman correlation scores for all pairs of features in a dataset. These methods can only detect monotonic relationship.

Correlations-stamped.png


   Correlation measure:
       Pairwise Pearson correlation.
       Pairwise Spearman correlation.
   Filter for finding attribute pairs.
   A list of attribute pairs with correlation coefficient. Press Finished to stop computation for large datasets.
   Access widget help and produce report.

Contoh

Correlations can be computed only for numeric (continuous) features, so we will use housing as an example data set. Load it in the File widget and connect it to Correlations. Positively correlated feature pairs will be at the top of the list and negatively correlated will be at the bottom.

Correlations-links.png


Go to the most negatively correlated pair, DIS-NOX. Now connect Scatter Plot to Correlations and set two outputs, Data to Data and Features to Features. Observe how the feature pair is immediately set in the scatter plot. Looks like the two features are indeed negatively correlated.

Correlations-Example.png


Referensi

Pranala Menarik