SPARK-16426 isotonic regression with duplicate features that produce NaNs | 64 ms | Passed |

antitonic regression prediction | 70 ms | Passed |

antitonic regression prediction with duplicate features | 71 ms | Passed |

increasing isotonic regression | 1.4 sec | Passed |

isotonic regression RDD prediction | 0.12 sec | Passed |

isotonic regression prediction | 67 ms | Passed |

isotonic regression prediction with duplicate features | 63 ms | Passed |

isotonic regression strictly decreasing sequence | 0.15 sec | Passed |

isotonic regression strictly increasing sequence | 0.15 sec | Passed |

isotonic regression with first element violating monotonicity | 83 ms | Passed |

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

isotonic regression with negative labels | 77 ms | Passed |

isotonic regression with size 0 | 0.12 sec | Passed |

isotonic regression with size 1 | 0.14 sec | Passed |

isotonic regression with unordered input | 70 ms | Passed |

model construction | 4 ms | Passed |

model save/load | 4.2 sec | Passed |

weighted isotonic regression | 81 ms | Passed |

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

weighted isotonic regression with weights lower than 1 | 76 ms | Passed |

weighted isotonic regression with zero weights | 76 ms | Passed |