Exemple #1
0
 def main(self, mode='defect', justDeltas=False):
   if mode == "defect":
     train_DF = createTbl(self.train, isBin=False)
     test_DF = createTbl(self.test, isBin=False)
     before = rforest(train=train_DF, test=test_DF)
     clstr = [c for c in self.nodes(train_DF._rows)]
     return patches(train=self.train,
                    test=self.test,
                    clusters=clstr,
                    prune=self.prune,
                    pred=before).newTable(justDeltas=justDeltas)
   elif mode == "models":
     train_DF = createTbl(self.train, isBin=False)
     test_DF = createTbl(self.test, isBin=False)
     before = rforest(train=train_DF, test=test_DF)
     clstr = [c for c in self.nodes(train_DF._rows)]
     return patches(train=self.train,
                    test=self.test,
                    clusters=clstr,
                    prune=self.prune,
                    models=True,
                    pred=before).newTable(justDeltas=justDeltas)
   elif mode == "config":
     train_DF = createTbl(self.train, isBin=False)
     test_DF = createTbl(self.test, isBin=False)
     before = rforest2(train=train_DF, test=test_DF)
     clstr = [c for c in self.nodes(train_DF._rows)]
     return patches(train=self.train,
                    test=self.test,
                    clusters=clstr,
                    name=self.name,
                    prune=self.prune,
                    pred=before,
                    config=True).newTable(justDeltas=justDeltas)
Exemple #2
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    def __init__(self,
                 train,
                 test,
                 clusters,
                 prune=False,
                 B=0.25,
                 verbose=False,
                 bin=False):
        if bin:
            self.train = createTbl(train, isBin=False)
            self.test = createTbl(test, isBin=False)
        else:
            self.train = createTbl(train, isBin=False)
            self.test = createTbl(test, isBin=True)

        self.clusters = clusters
        self.Prune = prune
        self.B = B
        self.mask = self.fWeight()
        self.write = verbose
        self.bin = bin
        if bin:
            self.pred = rforest2(self.train,
                                 self.test,
                                 smoteit=True,
                                 duplicate=True)
        else:
            self.pred = rforest(self.train,
                                self.test,
                                smoteit=True,
                                duplicate=True)
Exemple #3
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 def main(self, config=False):
     if not config:
         train_DF = createTbl(self.train, isBin=False)
         test_DF = createTbl(self.test, isBin=False)
         before = rforest(train=train_DF, test=test_DF)
         clstr = [c for c in self.nodes(train_DF._rows)]
         return patches(train=self.train,
                        test=self.test,
                        clusters=clstr,
                        prune=self.prune).newTable()
     else:
         train_DF = createTbl(self.train, isBin=False)
         test_DF = createTbl(self.test, isBin=False)
         before = rforest2(train=train_DF, test=test_DF)
         clstr = [c for c in self.nodes(train_DF._rows)]
         return patches(train=self.train,
                        test=self.test,
                        clusters=clstr,
                        prune=self.prune,
                        bin=True).newTable()
  def __init__(
          self, train, test, clusters, prune=False, B=0.25
          , verbose=False, bin=False):
    if bin:
      self.train = createTbl(train, isBin=False)
      self.test = createTbl(test, isBin=False)
    else:
      self.train = createTbl(train, isBin=False)
      self.test = createTbl(test, isBin=True)

    self.clusters = clusters
    self.Prune = prune
    self.B = B
    self.mask = self.fWeight()
    self.write = verbose
    self.bin = bin
    if bin:
      self.pred = rforest2(self.train, self.test, smoteit=True, duplicate=True)
    else:
      self.pred = rforest(self.train, self.test, smoteit=True, duplicate=True)
 def main(self, config=False):
   if not config:
     train_DF = createTbl(self.train, isBin=False)
     test_DF = createTbl(self.test, isBin=False)
     before = rforest(train=train_DF, test=test_DF)
     clstr = [c for c in self.nodes(train_DF._rows)]
     return patches(train=self.train,
                    test=self.test,
                    clusters=clstr,
                    prune=self.prune).newTable()
   else:
     train_DF = createTbl(self.train, isBin=False)
     test_DF = createTbl(self.test, isBin=False)
     before = rforest2(train=train_DF, test=test_DF)
     clstr = [c for c in self.nodes(train_DF._rows)]
     return patches(train=self.train,
                    test=self.test,
                    clusters=clstr,
                    prune=self.prune,
                    bin=True).newTable()
Exemple #6
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#! /Users/rkrsn/miniconda/bin/python
Exemple #7
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#! /Users/rkrsn/miniconda/bin/python