Description Usage Arguments Value Author(s) Examples

Generate random data from mixture Gaussian distribution.

1 | ```
mydata(n, d, mu = 0.8, portion = 1/2)
``` |

`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

1 2 3 4 5 6 7 8 |

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