code: def pubdev_2118():
      df = h2o.import_file(
          pyunit_utils.locate("smalldata/prostate/prostate.csv")
      )
      df["CAPSULE"] = df["CAPSULE"].asfactor()
  
      m = H2OGradientBoostingEstimator()
      m.train(
          x=df.names,
          y="CAPSULE",
          training_frame=df,
          validation_frame=df,
      )
  
      t = m.gains_lift()
      # print t.cell_values
  
      exp = [
          (
              "",
              1,
              0.010526315789473684,
              0.9656726269867583,
              2.4836601307189543,
              2.4836601307189543,
              1.0,
              0.9710687339136742,
              1.0,
              0.9710687339136742,
              0.026143790849673203,
              0.026143790849673203,
              148.36601307189542,
              148.36601307189542,
          ),
          (
              "",
              2,
              0.021052631578947368,
              0.9589343603635085,
              2.4836601307189543,
              2.4836601307189543,
              1.0,
              0.9628960864202921,
              1.0,
              0.9669824101669832,
              0.026143790849673203,
              0.05228758169934641,
              148.36601307189542,
              148.36601307189542,
          ),
          (
              "",
              3,
              0.031578947368421054,
              0.9507825529565218,
              2.4836601307189543,
              2.4836601307189543,
              1.0,
              0.95405241347286,
              1.0,
              0.9626724112689421,
              0.026143790849673203,
              0.0784313725490196,
              148.36601307189542,
              148.36601307189542,
          ),
          (
              "",
              4,
              0.042105263157894736,
              0.942267273985621,
              2.4836601307189543,
              2.4836601307189543,
              1.0,
              0.9471095592343903,
              1.0,
              0.9587816982603041,
              0.026143790849673203,
              0.10457516339869281,
              148.36601307189542,
              148.36601307189542,
          ),
          (
              "",
              5,
              0.05,
              0.930122612318471,
              2.4836601307189543,
              2.4836601307189543,
              1.0,
              0.9377545194004764,
              1.0,
              0.9554616173876999,
              0.0196078431372549,
              0.12418300653594772,
              148.36601307189542,
              148.36601307189542,
          ),
          (
              "",
              6,
              0.1,
              0.9044146521806046,
              2.4836601307189543,
              2.4836601307189543,
              1.0,
              0.9193294296626036,
              1.0,
              0.9373955235251517,
              0.12418300653594772,
              0.24836601307189543,
              148.36601307189542,
              148.36601307189542,
          ),
          (
              "",
              7,
              0.15,
              0.8446853133779267,
              2.4836601307189543,
              2.4836601307189543,
              1.0,
              0.8751891162377066,
              1.0,
              0.9166600544293366,
              0.12418300653594772,
              0.37254901960784315,
              148.36601307189542,
              148.36601307189542,
          ),
          (
              "",
              8,
              0.2,
              0.7961432054656624,
              2.4836601307189543,
              2.4836601307189543,
              1.0,
              0.822552825530283,
              1.0,
              0.8931332472045731,
              0.12418300653594772,
              0.49673202614379086,
              148.36601307189542,
              148.36601307189542,
          ),
          (
              "",
              9,
              0.3,
              0.6723258400857857,
              2.4836601307189543,
              2.4836601307189543,
              1.0,
              0.7354960586993771,
              1.0,
              0.8405875177028411,
              0.24836601307189543,
              0.7450980392156863,
              148.36601307189542,
              148.36601307189542,
          ),
          (
              "",
              10,
              0.4,
              0.4587689342692059,
              1.6993464052287583,
              2.287581699346405,
              0.6842105263157895,
              0.5612327297355235,
              0.9210526315789473,
              0.7707488207110117,
              0.16993464052287582,
              0.9150326797385621,
              69.93464052287584,
              128.7581699346405,
          ),
          (
              "",
              11,
              0.5,
              0.2941654313583412,
              0.7843137254901961,
              1.9869281045751637,
              0.3157894736842105,
              0.36138604514289685,
              0.8,
              0.6888762655973888,
              0.0784313725490196,
              0.9934640522875817,
              -21.568627450980394,
              98.69281045751637,
          ),
          (
              "",
              12,
              0.6,
              0.1936958406847592,
              0.06535947712418301,
              1.6666666666666667,
              0.02631578947368421,
              0.23661298765425717,
              0.6710526315789473,
              0.6134990526068669,
              0.006535947712418301,
              1.0,
              -93.4640522875817,
              66.66666666666667,
          ),
          (
              "",
              13,
              0.7,
              0.11690112068515252,
              0.0,
              1.4285714285714286,
              0.0,
              0.15563383142391402,
              0.575187969924812,
              0.5480897352950165,
              0.0,
              1.0,
              -100.0,
              42.85714285714286,
          ),
          (
              "",
              14,
              0.8,
              0.08004747799144096,
              0.0,
              1.25,
              0.0,
              0.09663009317659732,
              0.5032894736842105,
              0.49165728003021403,
              0.0,
              1.0,
              -100.0,
              25.0,
          ),
          (
              "",
              15,
              0.9,
              0.04735533377423584,
              0.0,
              1.1111111111111112,
              0.0,
              0.06444853566528014,
              0.4473684210526316,
              0.44418964176744363,
              0.0,
              1.0,
              -100.0,
              11.111111111111116,
          ),
          (
              "",
              16,
              1.0,
              0.009748409930340669,
              0.0,
              1.0,
              0.0,
              0.03071707428603298,
              0.4026315789473684,
              0.4028423850193026,
              0.0,
              1.0,
              -100.0,
              0.0,
          ),
      ]
      print(t.cell_values)
      mycomp(exp, t.cell_values)
  
      t = m.gains_lift(valid=True)
      mycomp(exp, t.cell_values)
  
      p = m.model_performance(df)
      t = p.gains_lift()
      mycomp(exp, t.cell_values)
  
      m = H2OGradientBoostingEstimator(nfolds=3, seed=1234)
      m.train(
          x=df.names,
          y="CAPSULE",
          training_frame=df,
          validation_frame=df,
      )
      t = m.gains_lift(xval=True)
      print(t.cell_values)
      exp2 = [
          (
              "",
              1,
              0.010526315789473684,
              0.9720357890880759,
              1.8627450980392157,
              1.8627450980392157,
              0.75,
              0.9760072931854437,
              0.75,
              0.9760072931854437,
              0.0196078431372549,
              0.0196078431372549,
              86.27450980392157,
              86.27450980392157,
          ),
          (
              "",
              2,
              0.021052631578947368,
              0.9621849870843923,
              1.8627450980392157,
              1.8627450980392157,
              0.75,
              0.9669374439725144,
              0.75,
              0.971472368578979,
              0.0196078431372549,
              0.0392156862745098,
              86.27450980392157,
              86.27450980392157,
          ),
          (
              "",
              3,
              0.031578947368421054,
              0.9490492319323595,
              1.8627450980392157,
              1.8627450980392157,
              0.75,
              0.9568784717485775,
              0.75,
              0.9666077363021786,
              0.0196078431372549,
              0.058823529411764705,
              86.27450980392157,
              86.27450980392157,
          ),
          (
              "",
              4,
              0.042105263157894736,
              0.9331874956273033,
              1.8627450980392157,
              1.8627450980392157,
              0.75,
              0.9412334873687302,
              0.75,
              0.9602641740688165,
              0.0196078431372549,
              0.0784313725490196,
              86.27450980392157,
              86.27450980392157,
          ),
          (
              "",
              5,
              0.05,
              0.9319212918270888,
              2.4836601307189543,
              1.9607843137254903,
              1.0,
              0.9326627755163045,
              0.7894736842105263,
              0.9559060585078936,
              0.0196078431372549,
              0.09803921568627451,
              148.36601307189542,
              96.07843137254903,
          ),
          (
              "",
              6,
              0.1,
              0.8704014317587268,
              2.2222222222222223,
              2.0915032679738563,
              0.8947368421052632,
              0.9064122080712612,
              0.8421052631578947,
              0.9311591332895773,
              0.1111111111111111,
              0.20915032679738563,
              122.22222222222223,
              109.15032679738563,
          ),
          (
              "",
              7,
              0.15,
              0.7994327310905681,
              1.3071895424836601,
              1.8300653594771241,
              0.5263157894736842,
              0.8237496530969899,
              0.7368421052631579,
              0.8953559732253816,
              0.06535947712418301,
              0.27450980392156865,
              30.718954248366014,
              83.00653594771241,
          ),
          (
              "",
              8,
              0.2,
              0.7409640897307539,
              1.8300653594771241,
              1.8300653594771241,
              0.7368421052631579,
              0.7797762313520376,
              0.7368421052631579,
              0.8664610377570455,
              0.0915032679738562,
              0.3660130718954248,
              83.00653594771241,
              83.00653594771241,
          ),
          (
              "",
              9,
              0.3,
              0.5970714663081699,
              1.5686274509803921,
              1.7429193899782136,
              0.631578947368421,
              0.6593952334847722,
              0.7017543859649122,
              0.7974391029996212,
              0.1568627450980392,
              0.5228758169934641,
              56.86274509803921,
              74.29193899782136,
          ),
          (
              "",
              10,
              0.4,
              0.430473955067175,
              1.4379084967320264,
              1.6666666666666667,
              0.5789473684210527,
              0.5094600228139071,
              0.6710526315789473,
              0.7254443329531925,
              0.1437908496732026,
              0.6666666666666666,
              43.790849673202636,
              66.66666666666667,
          ),
          (
              "",
              11,
              0.5,
              0.3161245366286738,
              0.9803921568627452,
              1.5294117647058825,
              0.39473684210526316,
              0.3786448086411368,
              0.6157894736842106,
              0.6560844280907814,
              0.09803921568627451,
              0.7647058823529411,
              -1.9607843137254832,
              52.941176470588246,
          ),
          (
              "",
              12,
              0.6,
              0.23218508200249308,
              0.9150326797385621,
              1.4270152505446625,
              0.3684210526315789,
              0.2812411359528033,
              0.5745614035087719,
              0.5936105460677851,
              0.0915032679738562,
              0.8562091503267973,
              -8.496732026143794,
              42.70152505446625,
          ),
          (
              "",
              13,
              0.7,
              0.14659241228908762,
              0.5228758169934641,
              1.2978524743230628,
              0.21052631578947367,
              0.18397544100232177,
              0.5225563909774437,
              0.5350912453441474,
              0.05228758169934641,
              0.9084967320261438,
              -47.71241830065359,
              29.785247432306285,
          ),
          (
              "",
              14,
              0.8,
              0.09234093116404647,
              0.45751633986928103,
              1.1928104575163399,
              0.18421052631578946,
              0.12081167570481807,
              0.48026315789473684,
              0.4833062991392313,
              0.0457516339869281,
              0.954248366013072,
              -54.2483660130719,
              19.281045751633986,
          ),
          (
              "",
              15,
              0.9,
              0.04771122966691487,
              0.13071895424836602,
              1.074800290486565,
              0.05263157894736842,
              0.06846481525965206,
              0.4327485380116959,
              0.43721280093038917,
              0.013071895424836602,
              0.9673202614379085,
              -86.9281045751634,
              7.4800290486565,
          ),
          (
              "",
              16,
              1.0,
              0.009938670599098145,
              0.32679738562091504,
              1.0,
              0.13157894736842105,
              0.027346092704593806,
              0.4026315789473684,
              0.39622613010780966,
              0.032679738562091505,
              1.0,
              -67.3202614379085,
              0.0,
          ),
      ]
      mycomp(exp2, t.cell_values)
  
      p = m.model_performance(df)
      t = p.gains_lift()
      mycomp(exp, t.cell_values)
  
file_path: h2o-3/h2o-py/tests/testdir_jira/pyunit_pubdev_2118.py
imports: from builtins import str
  from builtins import zip
  from builtins import range
  import sys
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.gbm import H2OGradientBoostingEstimator
label_desc: Use image node_id 2 for calling a global function with example usage: pubdev_2118() without return types