SPARK-16426 isotonic regression with duplicate features that produce NaNs | 74 ms | Passed |

antitonic regression prediction | 79 ms | Passed |

antitonic regression prediction with duplicate features | 72 ms | Passed |

increasing isotonic regression | 1.6 sec | Passed |

isotonic regression RDD prediction | 0.14 sec | Passed |

isotonic regression prediction | 76 ms | Passed |

isotonic regression prediction with duplicate features | 78 ms | Passed |

isotonic regression strictly decreasing sequence | 0.1 sec | Passed |

isotonic regression strictly increasing sequence | 0.1 sec | Passed |

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

isotonic regression with last element violating monotonicity | 0.11 sec | Passed |

isotonic regression with negative labels | 95 ms | Passed |

isotonic regression with size 0 | 0.11 sec | Passed |

isotonic regression with size 1 | 0.13 sec | Passed |

isotonic regression with unordered input | 87 ms | Passed |

model construction | 5 ms | Passed |

model save/load | 4.4 sec | Passed |

weighted isotonic regression | 82 ms | Passed |

weighted isotonic regression with negative weights | 0.14 sec | Passed |

weighted isotonic regression with weights lower than 1 | 81 ms | Passed |

weighted isotonic regression with zero weights | 78 ms | Passed |