Question

我有一个干净的数据集，其nan值为零，但是我在回归器上仍然遇到相同的错误。我的框架称为new_player_data

我尝试通过

查找任何内容

list(new_player_data.where(new_player_data.isna()).count() > 0)

返回

[假，假，假，假，假， False]

大约200次。我以为可能会有一些太大的浮动。我尝试过：

for i in new_player_data.columns[:]:
    if new_player_data[i].dtype == float:
        new_player_data[i] = round(new_player_data[i],2)

无论我得到什么：

regressor.fit(X_train, y_train)  
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-327-3a664017ddaa> in <module>
----> 1 regressor.fit(X_train, y_train)

/anaconda3/lib/python3.7/site-packages/sklearn/ensemble/forest.py in fit(self, X, y, sample_weight)
    248 
    249         # Validate or convert input data
--> 250         X = check_array(X, accept_sparse="csc", dtype=DTYPE)
    251         y = check_array(y, accept_sparse='csc', ensure_2d=False, dtype=None)
    252         if sample_weight is not None:

/anaconda3/lib/python3.7/site-packages/sklearn/utils/validation.py in check_array(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, warn_on_dtype, estimator)
    571         if force_all_finite:
    572             _assert_all_finite(array,
--> 573                                allow_nan=force_all_finite == 'allow-nan')
    574 
    575     shape_repr = _shape_repr(array.shape)

/anaconda3/lib/python3.7/site-packages/sklearn/utils/validation.py in _assert_all_finite(X, allow_nan)
     54                 not allow_nan and not np.isfinite(X).all()):
     55             type_err = 'infinity' if allow_nan else 'NaN, infinity'
---> 56             raise ValueError(msg_err.format(type_err, X.dtype))
     57 
     58 

ValueError: Input contains NaN, infinity or a value too large for dtype('float32').

关于我在这里还要检查的其他任何想法？不知所措

Answer 1

通过@gmds来获得答案，结果证明它是inf值，是通过

找到的

pd.options.mode.use_inf_as_na = True
infs = np.where(np.isinf(new_player_data))
infs
out: (array([], dtype=int64), array([], dtype=int64))

然后我就这样替换了它们

tidyverse

感谢gmds的定向帮助！

尽管删除了Python随机森林回归器，但nan值仍然出错

1 个答案: