def __init__(
self, pred=rforest, _smoteit=True, _n=-1, _tuneit=False, dataName=None, reps=1):
self.pred = pred
self.dataName = dataName
self.out, self.out_pred = [self.dataName], []
self._smoteit = _smoteit
self.train, self.test = self.categorize()
self.reps = reps
self._n = _n
self.tunedParams = None if not _tuneit \
else tuner(self.pred, self.train[_n])
self.headers = createTbl(
self.train[
self._n],
isBin=False,
bugThres=1).headers
def __init__(self,
pred=rforest,
_smoteit=True,
_n=-1,
_tuneit=False,
dataName=None,
reps=1):
self.pred = pred
self.dataName = dataName
self.out, self.out_pred = [self.dataName], []
self._smoteit = _smoteit
self.train, self.test = self.categorize()
self.reps = reps
self._n = _n
self.tunedParams = None if not _tuneit \
else tuner(self.pred, self.train[_n])
self.headers = createTbl(self.train[self._n], isBin=False,
bugThres=1).headers
def __init__(self, file='ant', tuned=True):
self.file = file
self.train = createTbl(data(dataName=self.file).train[-1], isBin=True)
self.test = createTbl(data(dataName=self.file).test[-1], isBin=True)
self.param = dEvol.tuner(rforest, data(dataName=self.file).train[-1]) if \
tuned else None
def __init__(self, file='ant'):
self.file = file
self.train = createTbl(data(dataName=self.file).train[-1], isBin=True)
self.test = createTbl(data(dataName=self.file).test[-1], isBin=True)
self.param = dEvol.tuner(rforest, data(dataName=self.file).train[-1])
