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ValueError: Input contains NaN, infinity or a value too large for dtype('float32') 即使没有类似的东西

[英]ValueError: Input contains NaN, infinity or a value too large for dtype('float32') even though there is none that is like it

I was trying to fit my dataset into the CART model, but I keep on getting ValueError: Input contains NaN, infinity or a value too large for dtype('float32').我试图将我的数据集放入 CART model,但我一直收到 ValueError:输入包含 NaN、无穷大或对于 dtype('float32') 来说太大的值。 as an error.作为一个错误。 error problem错误问题

I had already double, even triple checked the dataset and I have seen that it does not contain any NaN, infinity, or anything that counts as that.我已经对数据集进行了两次甚至三次检查,发现它不包含任何 NaN、无穷大或任何可以算作 NaN 的东西。 I have also double checked if there were any blanks, and there weren't.我还仔细检查了是否有任何空白,但没有。 I tried everything including the most famous thread here, but to no avail.我尝试了一切,包括这里最著名的线程,但无济于事。 What could I be doing wrong?我做错了什么?

Edit:编辑:

flood_tr=df.sample(frac=0.75,random_state=42)

flood_test=df.drop(flood_tr.index)

y = flood_tr['flood_height']  

mar_np = np.array(flood_tr['precipitation'])  (mar_cat, mar_cat_dict) = stattools.categorical(mar_np, drop=True, dictnames=True)   

mar_cat_pd = pd.DataFrame(mar_cat)  
X = pd.concat((flood_tr[['elev']], mar_cat_pd), axis = 1)

rfy = np.ravel(y) 

rf01 = RandomForestClassifier(n_estimators = 100, 
criterion="gini").fit(X,rfy) #<--- this is where i got the error

here is the data set I used https://www.kaggle.com/datasets/giologicx/aegisdataset这是我使用的数据集https://www.kaggle.com/datasets/giologicx/aegisdataset

Your dataset has values larger than float32 (single-precision).您的数据集的值大于 float32(单精度)。 I would recommend doing the following.我建议执行以下操作。

X.round(dec) X.round(dec)

where dec == decimal precision in between something like (2~5)其中 dec == 小数精度介于 (2~5) 之间

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