如何解决ValueError:输入包含NaN，无穷大或对于dtype('float64')而言太大的值 [英] How to resolve ValueError: Input contains NaN, infinity or a value too large for dtype('float64')

问题描述

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))

但是我得到了这个错误:

but I got this error:

回溯(最近通话最近):

Traceback (most recent call last): File "E:\thesis\sk-ANN.py", line 67, 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:

My data set has values in exponential form, like this:

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

mlp.fit(X_train，y_train) 和 predictions = mlp.predict(X_test) 有人请帮我如何解决这个问题

the same error occur at mlp.fit(X_train,y_train) and predictions=mlp.predict(X_test) Someone please help me how to resolve this problem

推荐答案

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

I guess there must be nan values in input data, so before scaling values set all nan to avg. of column or set to zero, refer this.

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