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 = []