def __init__(self, C, toter, maxIter, kernel='linear'):
ML.__init__(self, 'svm')
self.kernel = kernel
self.En = []
self.C = C
self.toter = toter
self.maxIter = maxIter
self.b = 0
self.alphas = None
self.kij = {}
def __init__(self,
alg,
features,
max_depth=sys.maxint,
min_sample=1,
min_e=0.01,
rf=False):
ML.__init__(self, alg)
self.alg = alg
self.features = features
self.max_depth = max_depth
self.min_sample = min_sample
self.min_e = min_e
self.rf = rf
self.model = None
self.error = 0
# self.split_A = []
self.best_split_func = self.split_func[self.alg]
def __init__(self):
ML.__init__(self, 'Random Forest')
pass
def __init__(self):
ML.__init__(self, 'weak')
self.model = None
self.error = 0
def __init__(self):
ML.__init__(self, 'DBGT')
def __init__(self, classify=True):
ML.__init__(self, 'BoostingTree')
self.classify = classify
self.fm = []
