# Predicting label rankings based on the naive Bayes ranking model

### Description

This function predicts the rankings given prior and conditional probabilities obtained from `model_nbr`

### Usage

1 |

### Arguments

`x` |
is |

`y` |
is |

`new.x` |
is a vector of new attributes |

`n` |
is a parameter of 'memory'; that is, how fast past gets forgotten. (see details of time_weights). |

### Details

This function predicts a ranking for `test.x`

attributes. It initially builds a model for naive Bayes algorithm that calculates priors and conditional label ranking probabilities and then use them to predict rankings. The attributes can be nominal or continuous data.

### Value

a numeric vector of ranking

### Examples

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