Correlation matrix

Correlation matrix
The standardized version of the Covariance Matrix.
The general layout is the same as that of the covariance matrix, but here, entry C[i, j] is the correlation coefficient of (xi, xj) (instead of their covariance).

The correlation matrix is defined as the average over all inputs of xxT
The Hessian is the second derivative of E with respect to w.
For linear nets, the Hessian is the same as the correlation matrix.

The default way of deleting missing data while calculating a correlation matrix is to exclude all cases that have missing data in at least one of the selected variables; that is, by casewise deletion of missing data.

Next they take this massive correlation matrix and use a support vector machine (SVM with soft margin, including a radial basis function "kernel trick") to classify each timeseries as belonging to a child (7-11 years old) or an adult ...

In practice, the correlation matrix of the data is constructed and the eigenvectors on this matrix are computed.

Many statistical and decision-making tools such as multidimensional scaling (MDS) and Principle component Analysis (PCA) are rely heavily on the finding of Eigen value of symmetric matrix of covariance or correlation matrix.

See also: Distribution, Variance, Regression, Data mining, Standard Deviation