Python SVM.predict_with_default_dumped_model示例

示例#1

文件： test-svm.py 项目： afcarl/toy-recommend-webpage

PROJECT_HOME = os.path.dirname(os.path.abspath(__file__)) + "/../"
sys.path.append(PROJECT_HOME)

from webapp.recommend.svm import SVM

model = SVM()

## load test data
data_filepath = os.path.dirname(
    __file__) + "/../../resources/data/test-data.tsv"
labels_filepath = os.path.dirname(
    __file__) + "/../../resources/data/test-label.tsv"
data = model.load_tsv_file(data_filepath)
labels = model.load_tsv_file(labels_filepath)

## restore model from file
result = model.predict_with_default_dumped_model(data)

num_true = 0
num_false = 0
for i in range(0, len(labels)):
    if labels[i] == result[i]:
        num_true += 1
    else:
        num_false += 1

print("# trues : %d" % (num_true))
print("# falses: %d" % (num_false))
print("accurary: %f" % (num_true / (num_true + num_false)))

示例#2

def test_predict_with_default_dumped_model():
    model = SVM()
    target = [0, 2, 1]
    result = model.predict_with_default_dumped_model(target)
    assert_equal(result, [3])