Gaussian Mixture
The Gaussian Mixture Model models the distribution of the data as a "mixture" of several populations, each of which can be described by a single multivariate normal distribution. An example of such a distribution is that of sizes among adults, which is described by the mixture of two distributions: the sizes of men, and those of women, each of which is approximately described by a normal distribution.
The maximum number of iterations to learn the model. The Gaussian Mixture model uses the Expectation-Maximization algorithm, which is iterative, each iteration running on all of the data. A higher value of this parameter will lead to a longer running time, but a more precise clustering. A value between 10 and 100 is recommended.
Used to generate reproducible results. 0 or no value means that no known seed is used (results will not be fully reproducible)