SPARK-16426 isotonic regression with duplicate features that produce NaNs | 73 ms | Passed |

antitonic regression prediction | 93 ms | Passed |

antitonic regression prediction with duplicate features | 80 ms | Passed |

increasing isotonic regression | 2 sec | Passed |

isotonic regression RDD prediction | 0.2 sec | Passed |

isotonic regression prediction | 81 ms | Passed |

isotonic regression prediction with duplicate features | 80 ms | Passed |

isotonic regression strictly decreasing sequence | 0.24 sec | Passed |

isotonic regression strictly increasing sequence | 0.13 sec | Passed |

isotonic regression with first element violating monotonicity | 0.1 sec | Passed |

isotonic regression with last element violating monotonicity | 0.22 sec | Passed |

isotonic regression with negative labels | 0.12 sec | Passed |

isotonic regression with size 0 | 0.17 sec | Passed |

isotonic regression with size 1 | 0.13 sec | Passed |

isotonic regression with unordered input | 0.1 sec | Passed |

model construction | 7 ms | Passed |

model save/load | 6.1 sec | Passed |

weighted isotonic regression | 74 ms | Passed |

weighted isotonic regression with negative weights | 0.11 sec | Passed |

weighted isotonic regression with weights lower than 1 | 82 ms | Passed |

weighted isotonic regression with zero weights | 93 ms | Passed |