# Path: django_ai/supervised_learning/models/svm.py
# class SVC(SupervisedLearningTechnique):
#     class Meta:
#     SVM_KERNEL_CHOICES = (
#         ('linear', "Linear"),
#         ('poly', "Polynomial"),
#         ('rbf', "RBF"),
#         ('linear', "Linear"),
#         ('sigmoid', "Sigmoid"),
#         ('precomputed', "Precomputed"),
#     )
#     def __init__(self, *args, **kwargs):
#     def __str__(self):
#     def get_engine_object(self):
#     def get_conf_dict(self):


import random
import numpy as np
from django.test import TestCase
from django_ai.supervised_learning.models import svm
#!/usr/bin/env python
# -*- coding: utf-8 -*-

"""
test_svm.py
------------

Tests for `django-ai.supervised_learning`\ 's `svm` module.
"""



class TestSVM(TestCase):

    def setUp(self):
        # Set the seeds
        random.seed(123456)
        np.random.seed(123456)
        # -> SVM 1

# Path: django_ai/supervised_learning/models/svm.py
# class SVC(SupervisedLearningTechnique):
#     class Meta:
#     SVM_KERNEL_CHOICES = (
#         ('linear', "Linear"),
#         ('poly', "Polynomial"),
#         ('rbf', "RBF"),
#         ('linear', "Linear"),
#         ('sigmoid', "Sigmoid"),
#         ('precomputed', "Precomputed"),
#     )
#     def __init__(self, *args, **kwargs):
#     def __str__(self):
#     def get_engine_object(self):
#     def get_conf_dict(self):


# Path: tests/apps/supervised_learning/test_svm.py
import random
import numpy as np
from django.test import TestCase
from django_ai.supervised_learning.models import svm

#!/usr/bin/env python
# -*- coding: utf-8 -*-

"""
test_svm.py
------------

Tests for `django-ai.supervised_learning`\ 's `svm` module.
"""



class TestSVM(TestCase):

    def setUp(self):
        # Set the seeds
        random.seed(123456)
        np.random.seed(123456)
        # -> SVM 1

        self.svm1, _ = svm.SVC.objects.get_or_create(