| 529 | |
| 530 | |
| 531 | class SVR(SvmModel, RegressorMixin): |
| 532 | _impl = 'epsilon_svr' |
| 533 | |
| 534 | def __init__(self, kernel='rbf', degree=3, gamma='auto', |
| 535 | coef0=0.0, C=1.0, epsilon=0.1, |
| 536 | tol=0.001, probability=False, |
| 537 | shrinking=False, cache_size=None, verbose=False, |
| 538 | max_iter=-1, n_jobs=-1, max_mem_size=-1, gpu_id=0): |
| 539 | super(SVR, self).__init__( |
| 540 | kernel=kernel, degree=degree, gamma=gamma, |
| 541 | coef0=coef0, C=C, nu=0., epsilon=epsilon, |
| 542 | tol=tol, probability=probability, class_weight=None, |
| 543 | shrinking=shrinking, cache_size=cache_size, verbose=verbose, |
| 544 | max_iter=max_iter, n_jobs=n_jobs, max_mem_size=max_mem_size, random_state=None, gpu_id=gpu_id |
| 545 | ) |
| 546 | |
| 547 | |
| 548 | class NuSVR(SvmModel, RegressorMixin): |
nothing calls this directly
no outgoing calls
no test coverage detected