Constraint on covariance matrices which defines type of matrices.

Possible values:

• Spherical A scaled identity matrix mu_k*I. There is the only parameter mu_k to be estimated for each matrix. The option may be used in special cases, when the constraint is relevant, or as a first step in the optimization (for example in case when the data is preprocessed with cv.PCA). The results of such preliminary estimation may be passed again to the optimization procedure, this time with CovarianceMatrixType='Diagonal'.
• Diagonal A diagonal matrix with positive diagonal elements. The number of free parameters is d for each matrix. This is most commonly used option yielding good estimation results.
• Generic A symmetric positively defined matrix. The number of free parameters in each matrix is about d^2/2. It is not recommended to use this option, unless there is pretty accurate initial estimation of the parameters and/or a huge number of training samples.
• Default Synonym for 'Diagonal'. This is the default.