(self, kernel, degree,
gamma, coef0, C, nu, epsilon,
tol, probability, class_weight,
shrinking, cache_size, verbose,
max_iter, n_jobs, max_mem_size, random_state, gpu_id)
| 56 | |
| 57 | class SvmModel(ThundersvmBase): |
| 58 | def __init__(self, kernel, degree, |
| 59 | gamma, coef0, C, nu, epsilon, |
| 60 | tol, probability, class_weight, |
| 61 | shrinking, cache_size, verbose, |
| 62 | max_iter, n_jobs, max_mem_size, random_state, gpu_id): |
| 63 | self.kernel = kernel |
| 64 | self.degree = degree |
| 65 | self.gamma = gamma |
| 66 | self.coef0 = coef0 |
| 67 | self.C = C |
| 68 | self.nu = nu |
| 69 | self.epsilon = epsilon |
| 70 | self.tol = tol |
| 71 | self.probability = probability |
| 72 | self.class_weight = class_weight |
| 73 | self.shrinking = shrinking |
| 74 | self.cache_size = cache_size |
| 75 | self.verbose = verbose |
| 76 | self.max_iter = max_iter |
| 77 | self.n_jobs = n_jobs |
| 78 | self.random_state = random_state |
| 79 | self.max_mem_size = max_mem_size |
| 80 | self.gpu_id = gpu_id |
| 81 | self.model = None |
| 82 | thundersvm.model_new.restype = c_void_p |
| 83 | # self.model = thundersvm.model_new(SVM_TYPE.index(self._impl)) |
| 84 | # if self.max_mem_size != -1: |
| 85 | # thundersvm.set_memory_size(c_void_p(self.model), self.max_mem_size) |
| 86 | |
| 87 | def __del__(self): |
| 88 | if self.model is not None: |
nothing calls this directly
no outgoing calls
no test coverage detected