Prediction.py 文件源码

def rforest2(train, test, tunings=None, smoteit=True, duplicate=True):
  "RF "
  # Apply random forest Classifier to predict the number of bugs.
  if smoteit:
    train = SMOTE(train, atleast=50, atmost=101, resample=duplicate)
  if not tunings:
    clf = RandomForestRegressor(n_estimators=100, random_state=1)
  else:
    clf = RandomForestRegressor(n_estimators=int(tunings[0]),
                                max_features=tunings[1] / 100,
                                min_samples_leaf=int(tunings[2]),
                                min_samples_split=int(tunings[3])
                                )
  train_DF = formatData(train)
  test_DF = formatData(test)
  features = train_DF.columns[:-2]
  klass = train_DF[train_DF.columns[-2]]
  # set_trace()
  clf.fit(train_DF[features], klass)
  preds = clf.predict(test_DF[test_DF.columns[:-2]])
  return preds