逆变换预测结果答案

【问题标题】：Inverse Transform Predicted Results逆变换预测结果
【发布时间】：2018-11-29 23:54:58
【问题描述】：

我有一个包含三列的训练数据 CSV（两列用于数据，第三列用于目标），并且我成功预测了测试 CSV 的目标列。问题是我需要将结果逆变换回字符串以进行进一步分析。下面是代码和错误。

from sklearn import datasets
from sklearn import svm
from sklearn.neighbors import KNeighborsClassifier
from sklearn.linear_model import LogisticRegression
from sklearn.cross_validation import train_test_split
from sklearn.preprocessing import LabelEncoder

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from collections import defaultdict

df_train = pd.read_csv('/Users/justinchristensen/Documents/Python_Education/SKLearn/Path_Training_Data.csv')
df_test = pd.read_csv('/Users/justinchristensen/Documents/Python_Education/SKLearn/Path_Test_Data.csv')

#Separate columns in training data set
x_train = df_train.iloc[:,:-1]
y_train = df_train.iloc[:,-1:]

#Separate columns in test data set
x_test = df_test.iloc[:,:-1]

#Initiate classifier
clf = svm.SVC(gamma=0.001, C=100)
le = LabelEncoder()

#Transform strings into integers
x_train_encoded = x_train.apply(LabelEncoder().fit_transform)
y_train_encoded = y_train.apply(LabelEncoder().fit_transform)
x_test_encoded = x_test.apply(LabelEncoder().fit_transform)

#Fit the model into the classifier
clf.fit(x_train_encoded,y_train_encoded)

#Predict test values
y_pred = clf.predict(x_test_encoded)

错误

NotFittedError
Traceback (most recent call last)
<ipython-input-38-09840b0071d5> in <module>()
      1 
----> 2 y_pred_inverse = le.inverse_transform(y_pred)

~/anaconda3/lib/python3.6/site-packages/sklearn/preprocessing/label.py in inverse_transform(self, y)
    146         y : numpy array of shape [n_samples]
    147         """
--> 148         check_is_fitted(self, 'classes_')
    149 
    150         diff = np.setdiff1d(y, np.arange(len(self.classes_)))

~/anaconda3/lib/python3.6/site-packages/sklearn/utils/validation.py in check_is_fitted(estimator, attributes, msg, all_or_any)
    766 
    767     if not all_or_any([hasattr(estimator, attr) for attr in attributes]):
--> 768         raise NotFittedError(msg % {'name': type(estimator).__name__})
    769 
    770 

NotFittedError: This LabelEncoder instance is not fitted yet. Call 'fit' with appropriate arguments before using this method.

【问题讨论】：

标签： python machine-learning scikit-learn sklearn-pandas inverse-transform

【解决方案1】：

您需要使用与转换目标相同的标签对象才能将它们取回。每次使用 Label Enocder 时，都会实例化一个新对象。使用相同的对象。

更改以下行

y_train_encoded = y_train.apply(le().fit_transform)
y_test_encoded = y_test.apply(le().fit_transform)

然后使用相同的对象来反转转换。您也可以查看first example here in the documentation 以供参考。

【讨论】：