标记编码报错ValueError: bad input shape ()
《Python机器学习经典实例》2.9小节中,想自己动手实践汽车特征评估质量,所以需要对数据进行预处理,其中代码有把字符串标记编码为对应的数字,如下代码
input_data = ['vhigh', 'vhigh', '2', '2', 'small', 'low']
input_data_encoded = [-1] * len(input_data)
for i,item in enumerate(input_data):
input_data_encoded[i] = int(label_encoder[i].transform(input_data[i]))
报错:
Traceback (most recent call last):
File "E:/17770426925/PythonLeaning/Machine-Learning/classifier/classifier.py", line 255, in <module>
input_data_encoded[i] = int(label_encoder[i].transform(input_data[i]))
File "D:\ProgramData\Anaconda3\lib\site-packages\sklearn\preprocessing\label.py", line 147, in transform
y = column_or_1d(y, warn=True)
File "D:\ProgramData\Anaconda3\lib\site-packages\sklearn\utils\validation.py", line 562, in column_or_1d
raise ValueError("bad input shape {0}".format(shape))
ValueError: bad input shape ()
所以由此看出,是label_encoder[i].transform(input_data[i])中input_data[i]输入的数值形式不对,需要将其改变成list,所以可对该代码进行改进:
for i, item in enumerate(input_data):
labels=[]
labels.append(input_data[i])
input_data_encoded[i] = int(label_encoder[i].transform(labels))
文章来源:NSGUF,欢迎分享,转载请保留出处