def test_load_model(self):
X, y, _ = datasets.csv2numpy(config.get('RandomForest_test', 'traindata'))
self.rf.fit(X, y)
newX, _, _ = datasets.csv2numpy(config.get('RandomForest_test', 'noveldata'))
prediction = self.rf.predict(newX)
self.rf.save_model(config.get('RandomForest_test', 'modelfile'))
newrf = RandomForest()
newrf.load_model(config.get('RandomForest_test', 'modelfile'))
self.assertTrue(numpy.array_equal(prediction, newrf.predict(newX)))
os.remove(config.get('RandomForest_test', 'modelfile'))
def test_load_model(self):
X, y, _ = datasets.csv2numpy(
config.get('RandomForest_test', 'traindata'))
self.rf.fit(X, y)
newX, _, _ = datasets.csv2numpy(
config.get('RandomForest_test', 'noveldata'))
prediction = self.rf.predict(newX)
self.rf.save_model(config.get('RandomForest_test', 'modelfile'))
newrf = RandomForest()
newrf.load_model(config.get('RandomForest_test', 'modelfile'))
self.assertTrue(numpy.array_equal(prediction, newrf.predict(newX)))
os.remove(config.get('RandomForest_test', 'modelfile'))
