【发布时间】:2019-09-26 20:33:10
【问题描述】:
我从我的数据集中选择了特征,然后当我尝试从我的数据集中选择这些特征时,我收到了这个错误。为什么会这样?
dataset = pd.read_csv('Banking Dataset.csv')
LabelEncoder1 = LabelEncoder()
independent_variables[:,1] = LabelEncoder1.fit_transform(independent_variables[:,1])
LabelEncoder2 = LabelEncoder()
independent_variables[:,2] = LabelEncoder2.fit_transform(independent_variables[:,2])
onehotencoder = OneHotEncoder(categorical_features=[1])
independent_variables = onehotencoder.fit_transform(independent_variables).toarray()
X_train, X_test, Y_train,Y_test = train_test_split(independent_variables,target_values ,test_size=0.25,random_state=0)
c = DecisionTreeClassifier(min_samples_split=100)
features =["CreditScore","Geography","Gender","Age","Tenure","Balance","NumOfProducts","HasCrCard","IsActiveMember","EstimatedSalary"]
X = X_train(features)
输出:
FutureWarning:不推荐使用非元组序列进行多维索引;使用arr[tuple(seq)] 而不是arr[seq]。将来这将被解释为数组索引arr[np.array(seq)],这将导致错误或不同的结果。
X_train=X_train[特征]
Traceback(最近一次调用最后一次):
X_train=X_train[features]
IndexError:只有整数、切片 (:)、省略号 (...)、numpy.newaxis (None) 和整数或布尔数组是有效的索引
Process finished with exit code 1
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标签: python deep-learning artificial-intelligence classification decision-tree