def _init_pyfeat(self):
# set up pyfeat glue class object
self._pyfeat = pyfeat.PyFeat(
self.pop_size, self.gens, self.ml, self.classification,
self.verbosity, self.max_stall, self.sel, self.surv,
self.cross_rate, self.otype, self.functions, self.max_depth,
self.max_dim, self.random_state, self.erc, self.obj, self.shuffle,
self.split, self.fb, self.scorer, self.feature_names,
self.backprop, self.iters, self.lr, self.batch_size,
self.n_threads, self.hillclimb, self.logfile)
def _init_pyfeat(self):
"""set up pyfeat glue class object"""
self._pyfeat = pyfeat.PyFeat(
self.pop_size, self.gens, self.ml, self.classification,
self.verbosity, self.max_stall, self.sel, self.surv,
self.cross_rate, self.root_xo_rate, self.otype, self.functions,
self.max_depth, self.max_dim, self.random_state, self.erc,
self.obj, self.shuffle, self.split, self.fb, self.scorer,
self.feature_names, self.backprop, self.iters, self.lr,
self.batch_size, self.n_threads, self.hillclimb, self.logfile,
self.max_time, self.use_batch, self.residual_xo, self.stagewise_xo,
self.softmax_norm, self.print_pop, self.normalize)
def __init__(self,
pop_size=100,
gens=100,
ml="LinearRidgeRegression",
classification=False,
verbosity=0,
max_stall=0,
sel="lexicase",
surv="nsga2",
cross_rate=0.5,
otype='a',
functions="",
max_depth=3,
max_dim=10,
random_state=0,
erc=False,
obj="fitness,complexity",
shuffle=False,
split=0.75,
fb=0.5,
scorer='',
feature_names="",
backprop=False,
iters=10,
lr=0.1,
batch_size=100,
n_threads=0,
hillclimb=False,
logfile="Feat.log"):
self.pop_size = pop_size
self.gens = gens
self.ml = ml.encode() if (isinstance(ml, str)) else ml
self.classification = classification
self.verbosity = verbosity
self.max_stall = max_stall
self.sel = sel.encode() if (isinstance(sel, str)) else sel
self.surv = surv.encode() if (isinstance(surv, str)) else surv
self.cross_rate = cross_rate
self.otype = otype.encode() if (isinstance(otype, str)) else otype
self.functions = functions.encode() if (isinstance(functions,
str)) else functions
self.max_depth = max_depth
self.max_dim = max_dim
self.random_state = int(random_state)
self.erc = erc
self.obj = obj.encode() if (isinstance(obj, str)) else obj
self.shuffle = shuffle
self.split = split
self.fb = fb
self.scorer = scorer.encode() if (isinstance(scorer, str)) else scorer
self.feature_names = feature_names.encode() if isinstance(
feature_names, str) else feature_names
self.backprop = bool(backprop)
self.iters = int(iters)
self.lr = float(lr)
if batch_size:
self.batch_size = int(batch_size)
else:
print('batch_size is None for some reason')
self.batch_size = 100
self.n_threads = int(n_threads)
self.hillclimb = bool(hillclimb)
self.logfile = logfile.encode() if isinstance(logfile,
str) else logfile
# if self.verbosity>0:
print('self.__dict__: ', self.__dict__)
self._pyfeat = pyfeat.PyFeat(
self.pop_size, self.gens, self.ml, self.classification,
self.verbosity, self.max_stall, self.sel, self.surv,
self.cross_rate, self.otype, self.functions, self.max_depth,
self.max_dim, self.random_state, self.erc, self.obj, self.shuffle,
self.split, self.fb, self.scorer, self.feature_names,
self.backprop, self.iters, self.lr, self.batch_size,
self.n_threads, self.hillclimb, self.logfile)