Python

Question

我正在尝试导出数据集的未编码版本，该版本使用 LabelEncoder（来自 sklearn.preprocessing，以启用机器学习算法的应用）进行编码，随后分成训练和测试数据集（train_test_split）。

我想将测试数据导出到 excel 但使用原始值。到目前为止，我发现的示例仅对一个变量使用 LabelEncoder 的 inverse_transform 方法。我想将它自动应用于首先编码的多个列。

这是一个示例数据：

# data
code = ('A B C D A B C D E F').split()
sp = ('animal bird animal animal animal bird animal animal bird thing').split()
res = ('yes, yes, yes, yes, no, no, yes, no, yes, no').split(", ")
 
data =pd.DataFrame({'code':code, 'sp':sp, 'res':res})
data

假设 'res' 是目标变量，'code' & 'sp' 是特征。

Answer 1

给你：

# data
code = ('A B C D A B C D E F').split()
sp = ('animal bird animal animal animal bird animal animal bird thing').split()
res = ('yes, yes, yes, yes, no, no, yes, no, yes, no').split(", ")
 
data = pd.DataFrame({'code':code, 'sp':sp, 'res':res})
data

# creating LabelEncoder object
from sklearn.preprocessing import LabelEncoder
le = LabelEncoder()

# encoding
dfe = pd.DataFrame()    # created empty dataframe for saving encoded values
for column in data.columns:
    dfe[column] = le.fit_transform(data[column])
dfe

# saving features
X = dfe[['code','sp']]

# saving target
y = dfe['res']

# splitting into training & test data
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=13)

X_train

# reversal of encoding
dfr_train = X_train.copy()
for column in X.columns:
    le.fit(data[column])   # you fit the column before it was encoded here

# now that python has the above encoding in its memory, we can ask it to reverse such 
# encoding in the corresponding column having encoded values of the split dataset

    dfr_train[column] = le.inverse_transform(X_train[column])
dfr_train

您可以对测试数据执行相同的操作。

# reversal of encoding of data
dfr_test = X_test.copy()
for column in X.columns:
    le.fit(data[column])
    dfr_test[column] = le.inverse_transform(X_test[column])
dfr_test

这里是导出的完整训练数据（特征+变量）：

# reverse encoding of target variable y
le.fit(data['res'])
dfr_train['res'] = le.inverse_transform(y_train)
dfr_train     # unencoded training data, ready for export

Python - 如何将使用 LabelEncoder 编码的数据在被 train_test_split 拆分后反转编码？

Python - How to reverse the encoding of data encoded with LabelEncoder after it has been split by train_test_split?

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