Description Usage Arguments Value Author(s) Examples
Generate random data from mixture Gaussian distribution.
1 | mydata(n, d, mu = 0.8, portion = 1/2)
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n |
The number of observations (sample size). |
d |
The number of variables (dimension). |
mu |
In the Gaussian mixture model, the first Gaussian is generated with zero mean and identity covariance matrix. The second Gaussian is generated with mean a d-dimensional vector with all mu and identity covariance matrix. |
portion |
The prior probability for the first Gaussian component. |
Return the data matrix with n rows and d + 1 columns. Each row represents a sample generated from the mixture Gaussian distribution. The first d columns are features and the last column is the class label of the corresponding sample.
Wei Sun, Xingye Qiao, and Guang Cheng
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