繁体   English   中英

如何解决ValueError:输入包含NaN,无穷大或对于dtype来说太大的值('float64')

[英]How to resolve ValueError: Input contains NaN, infinity or a value too large for dtype('float64')

所以我有这个代码:

    ####----Data----####
quest=pd.read_csv("inputFile.csv", names=["A1","A2",..."A200","Sim"])
print(quest.head())
    ####----Set up Data and Label----####
X=quest.drop('Sim',axis=1)
y=quest['Sim']
    ####----Train Test Split----####
X_train, X_test, y_train, y_test = train_test_split(X, y)
np.isfinite(X_train).any(), np.isfinite(y_train).any(),np.isfinite(X_test).any()
np.isnan(X_train).any(), np.isnan(y_train).any(), np.isnan(X_test).any()
    ####----Data Pre-Processing----####
scaler=StandardScaler()
 # Fit only to the training data
X_scaled=scaler.fit(X_train)
 # Now apply the transformations to the data:
X_train = scaler.transform(X_train)
X_test = scaler.transform(X_test)
    ####----Training the Model----####
mlp=MLPClassifier(hidden_layer_sizes=(13,13,13), max_iter=500)
mlp.fit(X_train,y_train)
print(mlp)
    ####----Predictions and Evaluation----####
predictions=mlp.predict(X_test)

print(confusion_matrix(y_test,predictions))
print(classification_report(y_test,predictions))

但是我收到了这个错误:

回溯(最近一次调用最后一次):文件“E:\\ thesis \\ sk-ANN.py”,第67行,in

X_scaled=scaler.fit(X_train)...
ValueError: Input contains NaN, infinity or a value too large for dtype('float64').

我的数据集具有指数形式的值,如下所示:

2.15E-06    -0.000556462    0.000197385 -0.000919   -0.000578077....

同样的错误发生在mlp.fit(X_train,y_train)predictions = mlp.predict(X_test)有人请帮我解决这个问题

我猜输入数据中必须有nan值,因此在缩放值之前将所有nan设置为avg。 列或设置为零,请参阅

暂无
暂无

声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.

 
粤ICP备18138465号  © 2020-2024 STACKOOM.COM