Exemplos de NuSVC.get_params em Python

Exemplo n.º 1

Arquivo: svm___NuSVCGetParams0___METACODE.py Projeto: frecklebars/Ryven

 def __init__(self, params):
     super(%CLASS%, self).__init__(params)
     tmp = NuSVC()
     params = tmp.get_params()
     for key in params:
         self.create_new_output(type_="data", label=key, pos=-1)
     del tmp
     self.create_new_output(type_="data", label="param dict", pos=-1)

Exemplo n.º 2

 def __init__(self, params):
     super(NuSVCSetParams_NodeInstance, self).__init__(params)
     tmp = NuSVC()
     params = tmp.get_params()
     for key in params:
         self.create_new_input(type_="data",
                               label=key,
                               widget_name="std line edit m",
                               widget_pos="besides",
                               pos=-1)
     del tmp

Exemplo n.º 3

Arquivo: SVM-kernel可分.py Projeto: PythonLinzi/My-Alrorithm-Library

''' kernel = ‘linear’, ‘poly’, ‘rbf’, ‘sigmoid’, ‘precomputed’ or a callable '''
''' gamma = 'auto' or 'scale' '''

import numpy as np
X = np.array([[-1, -1], [-2, -1], [1, 1], [2, 1]])
y = np.array([1, 1, 2, 2])

from sklearn.svm import NuSVC

# poly 多项式核函数
# degree [int, optional (default=3)]: Degree of the polynomial kernel function (‘poly’).
# Ignored by all other kernels.
clf = NuSVC(kernel='poly', degree=3, gamma='auto', nu=0.5, tol=0.001)
clf.fit(X, y)
print(clf.predict([[-0.8, -1]]))
print(clf.get_params())

# rbf 径向基核函数
clf = NuSVC(kernel='rbf', gamma='scale', nu=0.5, tol=1e-3)
clf.fit(X, y)
print(clf.predict([[-0.8, -1]]))

# sigmoid S型内核函数
clf = NuSVC(kernel='sigmoid', gamma='scale', tol=0.001)
clf.fit(X, y)
print(clf.predict([[-0.8, -1]]))

Exemplo n.º 4

Arquivo: models.py Projeto: heroxdream/information-retrieval

print 'LinearSVC precision test: {}'.format(lsvc_score_test)
print ''

lsvr = LinearSVR()
print 'LinearSVR config:'
print svc.get_params()
lsvr.fit(smr_train.feature_matrix, smr_train.labels)
lsvr_score_train = svc.score(smr_train.feature_matrix, smr_train.labels)
print 'LinearSVR precision train: {}'.format(lsvr_score_train)
lsvr_score_test = lsvr.score(smr_test.feature_matrix, smr_test.labels)
print 'LinearSVR precision test: {}'.format(lsvr_score_test)
print ''

nusvc = NuSVC()
print 'NuSVC config:'
print nusvc.get_params()
nusvc.fit(smr_train.feature_matrix, smr_train.labels)
nusvc_score_train = nusvc.score(smr_train.feature_matrix, smr_train.labels)
print 'NuSVC precision train: {}'.format(nusvc_score_train)
nusvc_score_test = nusvc.score(smr_test.feature_matrix, smr_test.labels)
print 'NuSVC precision test: {}'.format(nusvc_score_test)
print ''

nusvr = NuSVR()
print 'NuSVR config:'
print nusvr.get_params()
nusvr.fit(smr_train.feature_matrix, smr_train.labels)
nusvr_score_train = svc.score(smr_train.feature_matrix, smr_train.labels)
print 'NuSVR precision train: {}'.format(nusvr_score_train)
nusvr_score_test = nusvr.score(smr_test.feature_matrix, smr_test.labels)
print 'NuSVR precision test: {}'.format(nusvr_score_test)