VertexFrame daal_covariance_matrix

---

daal_covariance_matrix(self, data_column_names, matrix_name=None)

[BETA] Calculate covariance matrix for two or more columns.

Parameters:

data_column_names : list

The names of the column from which to compute the matrix. Names should refer to a single column of type vector, or two or more columns of numeric scalars.

matrix_name : unicode (default=None)

The name of the new matrix.

Returns:

: Frame

A matrix with the covariance values for the columns.

Uses Intel Data Analytics and Acceleration Library (DAAL) to compute covariance matrix.

Notes

This function applies only to columns containing numerical data.

Examples

Consider Frame my_frame, which contains the data

>>> my_frame.inspect()
 [#]  idnum  x1   x2   x3   x4
===============================
[0]      0  1.0  4.0  0.0  -1.0
[1]      1  2.0  3.0  0.0  -1.0
[2]      2  3.0  2.0  1.0  -1.0
[3]      3  4.0  1.0  2.0  -1.0
[4]      4  5.0  0.0  2.0  -1.0

my_frame.daal_covariance_matrix computes the covariance on each pair of columns in the user-provided list.

>>> cov_matrix = my_frame.daal_covariance_matrix(my_frame.column_names)
[===Job Progress===]

The resulting table (specifying all columns) is:

>>> cov_matrix.inspect()
[#]  idnum  x1    x2    x3    x4
=================================
[0]    2.5   2.5  -2.5   1.5  0.0
[1]    2.5   2.5  -2.5   1.5  0.0
[2]   -2.5  -2.5   2.5  -1.5  0.0
[3]    1.5   1.5  -1.5   1.0  0.0
[4]    0.0   0.0   0.0   0.0  0.0