SMOTE - 无法将字符串转换为浮点数 [英] SMOTE - could not convert string to float

问题描述

我想我在下面的代码中遗漏了一些东西.

I think I'm missing something in the code below.

from sklearn.model_selection import train_test_split
from imblearn.over_sampling import SMOTE


# Split into training and test sets

# Testing Count Vectorizer

X = df[['Spam']]
y = df['Value']

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=40)
X_resample, y_resampled = SMOTE().fit_resample(X_train, y_train)


sm =  pd.concat([X_resampled, y_resampled], axis=1)

因为我收到错误

ValueError: 无法将字符串转换为浮点数:--->19 X_resampled, y_resampled = SMOTE().fit_resample(X_train, y_train)

ValueError: could not convert string to float: ---> 19 X_resampled, y_resampled = SMOTE().fit_resample(X_train, y_train)

数据示例为

Spam                                             Value
Your microsoft account was compromised             1
Manchester United lost against PSG                 0
I like cooking                                     0

我会考虑转换训练集和测试集以解决导致错误的问题，但我不知道如何同时应用这两者.我在谷歌上试过一些例子，但没有解决问题.

I'd consider to transform both train and test sets to fix the issue which is causing the error, but I don't know how to apply to both. I've tried some examples on google, but it hasn't fixed the issue.

推荐答案

在应用 SMOTE 之前将文本数据转换为数字，如下所示.

convert text data to numeric before applying SMOTE , like below.

from sklearn.feature_extraction.text import CountVectorizer

vectorizer = CountVectorizer()
vectorizer.fit(X_train.values.ravel())
X_train=vectorizer.transform(X_train.values.ravel())
X_test=vectorizer.transform(X_test.values.ravel())
X_train=X_train.toarray()
X_test=X_test.toarray()

然后添加您的 SMOTE 代码

and then add your SMOTE code

x_train = pd.DataFrame(X_train)
X_resample, y_resampled = SMOTE().fit_resample(X_train, y_train)

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