SMOTE - 无法将字符串转换为浮点数

Question

我想我在下面的代码中遗漏了一些东西。

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)

当我收到错误时

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）

数据示例是

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来解决导致错误的问题，但我不知道如何应用于两者。我在谷歌上尝试了一些例子，但它没有解决问题。

Answer 1

在应用 SMOTE 之前将文本数据转换为数字，如下所示。

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

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