def get_records():
'''
get records from database
'''
conn = module_io.db_connect()
query = module_io.load_sql("../sql/query-features-train.sql")
records = module_io.db_query(conn, query)
return records
def get_records():
'''
get records from database
'''
conn = module_io.db_connect()
query = module_io.load_sql("../sql/query-features-train.sql")
records = module_io.db_query(conn, query)
return records
import module_io
from sklearn.ensemble import RandomForestClassifier
if __name__=="__main__":
# look backwared & look forward
look_backward = 29
look_forward = 4
# get records from database
print "getting features from database"
conn = module_io.db_connect()
query = module_io.load_sql("../sql/query-features-test.sql")
records = module_io.db_query(conn, query)
# load model
classifier = module_io.load_model("../model/benchmark.pickle")
# clean features
features = []
for record in records:
vector_feature = list(record[1:])
for index in range(len(vector_feature)):
if vector_feature[index] is None:
vector_feature[index] = 0
features.append(vector_feature)
# get features
range_test = features[look_backward:(-look_forward)]
features_test = []
for index in range(look_backward, len(features) - look_forward):
import module_io
from sklearn.ensemble import RandomForestClassifier
if __name__ == "__main__":
# look backwared & look forward
look_backward = 29
look_forward = 4
# get records from database
print "getting features from database"
conn = module_io.db_connect()
query = module_io.load_sql("../sql/query-features-test.sql")
records = module_io.db_query(conn, query)
# load model
classifier = module_io.load_model("../model/benchmark.pickle")
# clean features
features = []
for record in records:
vector_feature = list(record[1:])
for index in range(len(vector_feature)):
if vector_feature[index] is None:
vector_feature[index] = 0
features.append(vector_feature)
# get features
range_test = features[look_backward:(-look_forward)]
features_test = []
for index in range(look_backward, len(features) - look_forward):