def test_train():
model = SVM()
data_filepath = os.path.dirname(__file__) + "/data/test-data.tsv"
labels_filepath = os.path.dirname(__file__) + "/data/test-data-label.tsv"
data = model.load_tsv_file(data_filepath)
labels = model.load_tsv_file(labels_filepath)
clf = model.train(data, labels)
def test_dump_model():
model = SVM()
data_filepath = os.path.dirname(__file__) + "/data/test-data.tsv"
labels_filepath = os.path.dirname(__file__) + "/data/test-data-label.tsv"
data = model.load_tsv_file(data_filepath)
labels = model.load_tsv_file(labels_filepath)
clf = model.train(data, labels)
pickled_filepath = os.path.dirname(__file__) + "/data/trained-svm.pickle"
pickled_string = model.dump_model(pickled_filepath)
assert (isinstance(pickled_filepath, str))
assert_equal(len(pickled_string), 1734)
#!/usr/bin/env python3
#coding:utf-8
import os
import sys
PROJECT_HOME = os.path.dirname(os.path.abspath(__file__)) + "/../"
sys.path.append(PROJECT_HOME)
from webapp.recommend.svm import SVM
## traininn
model = SVM()
data_filepath = os.path.dirname(
__file__) + "/../../resources/data/train-data.tsv"
labels_filepath = os.path.dirname(
__file__) + "/../../resources/data/train-label.tsv"
data = model.load_tsv_file(data_filepath)
labels = model.load_tsv_file(labels_filepath)
clf = model.train(data, labels)
## save default model
model.dump_default_model()