Turi Create Error : 'module' object not callable
Turi Create Error : 'module' object not callable
我正在尝试在 Turi Create 中实施最近邻分类器,但是我不确定我遇到的这个错误。当我创建实际模型时会发生此错误。如果有帮助,我正在使用 python 3.6。
错误:
Traceback (most recent call last):
File "/Users/PycharmProjects/turi/turi.py", line 51, in <module>
iris_cross()
File "/Users/PycharmProjects/turi/turi.py", line 37, in iris_cross
clf = tc.nearest_neighbor_classifier(train_data, target='4', features=features)
TypeError: 'module' object is not callable
代码:
import turicreate as tc
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn import datasets
import time
import numpy as np
#Iris Classification Cross Validation
def iris_cross():
iris = datasets.load_iris()
features = ['0','1','2','3']
target = iris.target_names
x = iris.data
y = iris.target.astype(int)
undata = np.column_stack((x,y))
data = tc.SFrame(pd.DataFrame(undata))
print(data)
train_data, test_data = data.random_split(.8)
clf = tc.nearest_neighbor_classifier(train_data, target='4', features=features)
print('done')
iris_cross()
您必须实际调用 nearest_neighbor_classifier 的 create()
方法。见 library API.
运行 下面一行代码代替:
clf = tc.nearest_neighbor_classifier.create(train_data, target='4', features=features)
我正在尝试在 Turi Create 中实施最近邻分类器,但是我不确定我遇到的这个错误。当我创建实际模型时会发生此错误。如果有帮助,我正在使用 python 3.6。
错误:
Traceback (most recent call last):
File "/Users/PycharmProjects/turi/turi.py", line 51, in <module>
iris_cross()
File "/Users/PycharmProjects/turi/turi.py", line 37, in iris_cross
clf = tc.nearest_neighbor_classifier(train_data, target='4', features=features)
TypeError: 'module' object is not callable
代码:
import turicreate as tc
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn import datasets
import time
import numpy as np
#Iris Classification Cross Validation
def iris_cross():
iris = datasets.load_iris()
features = ['0','1','2','3']
target = iris.target_names
x = iris.data
y = iris.target.astype(int)
undata = np.column_stack((x,y))
data = tc.SFrame(pd.DataFrame(undata))
print(data)
train_data, test_data = data.random_split(.8)
clf = tc.nearest_neighbor_classifier(train_data, target='4', features=features)
print('done')
iris_cross()
您必须实际调用 nearest_neighbor_classifier 的 create()
方法。见 library API.
运行 下面一行代码代替:
clf = tc.nearest_neighbor_classifier.create(train_data, target='4', features=features)