问题描述
我正在尝试使用 OneClassSVM 检测数据集的异常值,我的代码如下
from sklearn.svm import OneClassSVM
import pandas as pd
input_file = "training.csv"
training_data = pd.read_csv(input_file)
X = training_data[['header1','header2','header3']].values
model = OneClassSVM(gamma='auto').fit(X)
但我收到以下错误:
> Traceback (most recent call last): File
> "C:/Users/user1/PycharmProjects/sv/main.py",line 13,in <module>
> model = svm.OneClassSVM(gamma='auto').fit(X) File "C:\Users\user1\PycharmProjects\sv\venv\lib\site-packages\sklearn\svm\_classes.py",> line 1376,in fit
> super().fit(X,np.ones(_num_samples(X)),File "C:\Users\user1\PycharmProjects\sv\venv\lib\site-packages\sklearn\svm\_base.py",> line 169,in fit
> X,y = self._validate_data(X,y,dtype=np.float64,File "C:\Users\user1\PycharmProjects\sv\venv\lib\site-packages\sklearn\base.py",> line 433,in _validate_data
> X,y = check_X_y(X,**check_params) File "C:\Users\user1\PycharmProjects\sv\venv\lib\site-packages\sklearn\utils\validation.py",> line 63,in inner_f
> return f(*args,**kwargs) File "C:\Users\user1\PycharmProjects\sv\venv\lib\site-packages\sklearn\utils\validation.py",> line 814,in check_X_y
> X = check_array(X,accept_sparse=accept_sparse,File "C:\Users\user1\PycharmProjects\sv\venv\lib\site-packages\sklearn\utils\validation.py",> line 616,in check_array
> array = np.asarray(array,order=order,dtype=dtype) File "C:\Users\user1\PycharmProjects\sv\venv\lib\site-packages\numpy\core\_asarray.py",> line 102,in asarray
> return array(a,dtype,copy=False,order=order) ValueError: Could not convert string to float: 'SDS'
>
> Process finished with exit code 1
有人可以帮忙解决这个问题吗?
解决方法
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