问如何修复“输入包含NaN、无穷大或对于dtype(‘float64’)来说太大的值。”在计算MSLE时

EN

from sklearn.datasets import load_boston
dataset = load_boston()

import pandas as pd
df = pd.DataFrame(dataset.data, columns=dataset.feature_names, )

df["MEDV"] = dataset.target

#tried this, no difference
df = df.reset_index()

df.isnull().sum()
#No missing values

df.dtypes
# all float64

cols = ["LSTAT", "RM"]
X = df[cols]#.astype(np.float)
y = df["MEDV"]#.astype(np.float)

from sklearn.linear_model import LinearRegression
slr = LinearRegression()
slr.fit(X, y)
y_pred = slr.predict(X)

np.all(np.isfinite(X))
# true
np.all(np.isfinite(y))
#true

np.all(np.isfinite(y_pred))
#true

from sklearn.metrics import mean_squared_error
mse = mean_squared_error(y, y_pred)
print(mse)

from sklearn.metrics import mean_squared_log_error
# THIS produces the error message:
msle = mean_squared_log_error(y, y_pred)
print(msle)