`gendata.mix`

generates data (both training and test data) from
Bayesian mixture model. The prior distribution of "theta" is uniform(0,1). The value
of "alpha" is given by argument `alpha`

, which controls the the overall
relationship between the response and the predictor variables.

1 | ```
gendata.mix (n1,n2,m1,m2,p,alpha,prob.y=c(0.9,0.1))
``` |

`n1` |
the number of class 1 in training data |

`n2` |
the number of class 2 in training data |

`m1` |
the number of class 1 in test data |

`m2` |
the number of class 2 in test data |

`p` |
the number of features |

`alpha` |
a parameter controlling the dependency between the features and the response |

`prob.y` |
a vector of two elements specifying the probabilities of the response being 1 in each group |

`train` |
the training data, with the row standing for the cases and the first column being the response |

`test` |
the test data, of the same format as "train" |

`train_predict_mix`

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