Pearson Similarity (Beta)

The Pearson correlation coefficient is a measure of linear correlation between two sets of data. It is the ratio between the covariance of two variables and the product of their standard deviations.

The formula for calculating the Pearson correlation coefficient is as follows:

$$\rho _{X,Y}={\frac {\operatorname {cov} (X,Y)}{\sigma _{X}\sigma _{Y}}}$$

This algorithm is implemented as a user-defined function. You need to follow the steps in Add a User-Defined Function to add the function to GSQL. After adding the function, you can call it in any GSQL query in the same way as a built-in GSQL function.

Specifications

tg_pearson_similarity_accum(A, B)

Parameters

Name	Description	Data type
A	An n-dimensional vector denoted by a ListAccum of length n	ListAccum<INT/UINT/FLOAT/DOUBLE>
B	An n-dimensional vector denoted by a ListAccum of length n	ListAccum<INT/UINT/FLOAT/DOUBLE>

Return value

The Pearson correlation coefficient between the two vectors.

Example

Query

CREATE QUERY pearson_example() FOR GRAPH social { 
  ListAccum<INT> @@a = [1, 2, 3];
  ListAccum<INT> @@b = [2, 2, 3];
  double pearson_similarity = tg_pearson_similarity_accum(@@a, @@b);
  PRINT pearson_similarity; 
}

Result

  {
    "pearson_similarity": 0.86603
  }