ValueError：无法将字符串转换为浮点数：'f'

Question

要使用决策树算法。但是由于出现ValueError：错误而无法将字符串转换为float：'f'。请帮助我，我在哪里想念。

import numpy as np
import pandas as pd

#Plotting
import matplotlib.pyplot as plt

#Machine Learning Libraries

from sklearn.neighbors import KNeighborsClassifier
from sklearn import tree   
from sklearn.model_selection import train_test_split

from sklearn import metrics
from sklearn.metrics import accuracy_score
from sklearn.metrics import confusion_matrix



#Loading Dataset
My_dataset = pd.read_csv('mushrooms.csv');
print (My_dataset.head())
print (My_dataset.shape)
#Dividing the datasets into Indicator and Predictor Variables
My_data = My_dataset.iloc[:,1:23].values
My_target = My_dataset.iloc[:,0].values
print()
print(My_data)
print()
print(My_target)
mushroom_train,mushroom_test,mushroomtarget_train,mushroomtarget_test = \
train_test_split(My_data,My_target, test_size = 0.3)

DT_Model_Mushroom = tree.DecisionTreeClassifier() 
DT_Model_Mushroom_Fitted = DT_Model_Mushroom.fit(mushroom_train, mushroomtarget_train)

错误：

Error
return array(a, dtype, copy=False, order=order)

ValueError: could not convert string to float: 'f'

Answer 1

scikit学习中的决策树分类器不将字符串作为输入。

如果数据中包含分类变量，则应事先对其进行编码（使用sklearn编码器之一，例如One hot encoder，Ordinal Encoder，...）

如果您的数据中没有分类变量，则熊猫可能无法正确将类型归因于您的列。如果发生这种情况，则应使用read_csv函数的“ dtype”参数。