Question

运行以下代码时出现错误：

def isolation_tree(data, counter=0, max_depth=50, random_subspace=False):

    # End Loop
    if (counter == max_depth) or data.shape[0]<=1:
        classification = classify_data(data)
        return classification

    else:
        # Counter
        counter +=1

        # Select feature
        split_column = select_feature(data)

        # Select value
        split_value = select_value(data, split_column)

        # Split data
        data_below, data_above = split_data(data, split_column, split_value)

        # instantiate sub-tree      
        question = "{} <= {}".format(split_column, split_value)
        sub_tree = {question: []}

        # Recursive part
        below_answer = isolation_tree(data_below, counter, max_depth=max_depth)
        above_answer = isolation_tree(data_above, counter, max_depth=max_depth)

        if below_answer == above_answer:
            sub_tree = below_answer
        else:
            sub_tree[question].append(below_answer)
            sub_tree[question].append(above_answer)

        return sub_tree

tree = isolation_tree(df.head(6), max_depth=1)
pprint(tree)

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-25-487c502563a5> in <module>
----> 1 tree = isolation_tree(df.head(256), max_depth=1)
      2 pprint(tree)

<ipython-input-24-d71e3aed4b2a> in isolation_tree(data, counter, max_depth, random_subspace)
     25         # Recursive part
     26         below_answer = isolation_tree(data_below, counter,max_depth=max_depth)
---> 27         above_answer = isolation_tree(data_above, counter,max_depth=max_depth)
     28 
     29         if below_answer == above_answer:

<ipython-input-24-d71e3aed4b2a> in isolation_tree(data, counter, max_depth, random_subspace)
      3     # End Loop
      4     if (counter == max_depth) or data.shape[0]<=1:
----> 5         classification = classify_data(data)
      6         return classification
      7 

<ipython-input-15-26b1d48eb27a> in classify_data(data)
      4     unique_classes, counts_unique_classes = np.unique(label_column, return_counts=True)
      5 
----> 6     index = counts_unique_classes.argmax()
      7     classification = unique_classes[index]
      8 

ValueError: attempt to get argmax of an empty sequence

Answer 1

函数classify_data中的行

unique_classes, counts_unique_classes = np.unique(label_column, return_counts=True)

counts_unique_classes返回一个空的numpy数组。重现此内容的简单方法如下。

import numpy as np
a = np.array([])
a.argmax()

错误

Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ValueError: attempt to get argmax of an empty sequence

因此，在运行.argmax()之前，请添加一些条件，例如

if counts_unique_classes.size == 0:
    # Do something

如果您不应该获取空序列/数组，请尝试添加日志以查看传递给classify_data函数的数据。

Answer 2

我尝试了此操作，但返回了相同的错误：

def classify_data(data):

    label_column = data.values[:, -1]
    unique_classes, counts_unique_classes = np.unique(label_column, return_counts=True)

    index = counts_unique_classes.argmax()
    classification = unique_classes[index]

    return classification

我得到了ValueError：运行以下代码时尝试获取空序列的argmax

2 个答案: