Python sklearn kaggle/titanic 教程在最后一个特征尺度上失败

Question

我正在学习本教程：http://ahmedbesbes.com/how-to-score-08134-in-titanic-kaggle-challenge.html

一切顺利，直到我到达中间部分的最后部分：

如您所见，特征运行ge 在不同的区间。让我们在单位间隔内对所有这些进行归一化。所有这些，除了我们提交时需要的 PassengerId

In [48]:
>>> def scale_all_features():

>>>     global combined

>>>     features = list(combined.columns)
>>>     features.remove('PassengerId')
>>>     combined[features] = combined[features].apply(lambda x: x/x.max(), axis=0)

>>>     print 'Features scaled successfully !'

In [49]:
>>> scale_all_features()

特征缩放成功！

尽管在我的 python 脚本中逐字输入：

#Cell 48
GreatDivide.split()
def scale_all_features():

    global combined

    features = list(combined.columns)
    features.remove('PassengerId')
    combined[features] = combined[features].apply(lambda x: x/x.max(), axis=0)

    print 'Features scaled successfully !'

#Cell 49
GreatDivide.split()
scale_all_features()

它一直给我一个错误：

--------------------------------------------------48--------------------------------------------------
--------------------------------------------------49--------------------------------------------------
Traceback (most recent call last):
  File "KaggleTitanic[2-FE]--[01].py", line 350, in <module>
    scale_all_features()
  File "KaggleTitanic[2-FE]--[01].py", line 332, in scale_all_features
    combined[features] = combined[features].apply(lambda x: x/x.max(), axis=0)
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/frame.py", line 4061, in apply
    return self._apply_standard(f, axis, reduce=reduce)
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/frame.py", line 4157, in _apply_standard
    results[i] = func(v)
  File "KaggleTitanic[2-FE]--[01].py", line 332, in <lambda>
    combined[features] = combined[features].apply(lambda x: x/x.max(), axis=0)
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/ops.py", line 651, in wrapper
    return left._constructor(wrap_results(na_op(lvalues, rvalues)),
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/ops.py", line 592, in na_op
    result[mask] = op(x[mask], y)
TypeError: ("unsupported operand type(s) for /: 'str' and 'str'", u'occurred at index Ticket')

这里有什么问题？之前的所有 49 个部分运行都没有问题，所以如果我遇到错误，它现在应该已经显示出来了，对吧？

Answer 1

您可以使用以下方法帮助确保数学转换仅发生在数字列上。

numeric_cols = combined.columns[combined.dtypes != 'object']
combined.loc[:, numeric_cols] = combined[numeric_cols] / combined[numeric_cols].max()

不需要那个apply函数。

Python sklearn kaggle/titanic 教程在最后一个特征尺度上失败

Python sklearn kaggle/titanic tutorial fails on the last feature scale

python

pandas

machine-learning

scikit-learn

kaggle