SPARK-16426 isotonic regression with duplicate features that produce NaNs | 0.5 sec | Passed |

antitonic regression prediction | 0.21 sec | Passed |

antitonic regression prediction with duplicate features | 0.17 sec | Passed |

increasing isotonic regression | 0.44 sec | Passed |

isotonic regression RDD prediction | 0.43 sec | Passed |

isotonic regression prediction | 76 ms | Passed |

isotonic regression prediction with duplicate features | 0.38 sec | Passed |

isotonic regression strictly decreasing sequence | 71 ms | Passed |

isotonic regression strictly increasing sequence | 76 ms | Passed |

isotonic regression with first element violating monotonicity | 84 ms | Passed |

isotonic regression with last element violating monotonicity | 78 ms | Passed |

isotonic regression with negative labels | 1 sec | Passed |

isotonic regression with size 0 | 0.16 sec | Passed |

isotonic regression with size 1 | 65 ms | Passed |

isotonic regression with unordered input | 1.9 sec | Passed |

model construction | 4 ms | Passed |

model save/load | 0.81 sec | Passed |

weighted isotonic regression | 73 ms | Passed |

weighted isotonic regression with negative weights | 1.4 sec | Passed |

weighted isotonic regression with weights lower than 1 | 0.31 sec | Passed |

weighted isotonic regression with zero weights | 86 ms | Passed |