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

Question

这是我的代码，它应该是一个简单的回归算法。该数据集有大约500个样本，每个样本有12个因子。我收到了这个错误：

ValueError：输入包含NaN，无穷大或对于dtype（'float64'）而言太大的值。

码：

dataset = pd.read_csv('/Users/chrisrivas/Documents/Andrew     Haines/Datasets/GRD.csv', header=None, sep=',')

#coverts dataset into 2d array of values and seperates target column
#[1st to: last rows, and 1st to: 12th columns ]
samples = dataset.loc[:, 1:12].values
targets = dataset[13].values

print(samples)
print(targets)

#training and testing of dataset
X_train, X_test, y_train, y_test = cross_validation.train_test_split(
samples, targets, test_size=0.35, random_state=0)

knn = KNeighborsClassifier(n_neighbors=1)
knn.fit(X_train, y_train)

y_pred = knn.predict(X_test)

#calculates accuracy of algorithm    
print("Test set score: {:.2f}%".format(np.mean(y_pred == y_test)*100))

#opens new data for algorithm to make classification predictions 
dataset2 = pd.read_csv('/Users/chrisrivas/Documents/Datasets/GoldRushDataset-41.csv', header=None, sep=',').values

#continues to loop for each sample and their classification prediction
for sample in dataset2:
    prediction = knn.predict([sample])
    print("Prediction: {}".format(prediction))
    print('    ')    

#other format for predictions: all at a time in array
prediction = knn.predict(dataset2)
print("Prediction: {}".format(prediction))

Answer 1

你在数据集2中检查过NaNs（不是数字）吗？例如。与dataset2.isnull().values.any()？

可能导致错误的另一个原因是：您需要以与处理训练数据相同的方式处理样本：

knn.predict(dataset2.loc[:, 1:12].values)