我在数据集中有506个点。我必须从该数据生成随机样本，例如我必须选择303点而不进行替换，而剩下的203点我需要从这303点中进行选择。
我已经编写了以下代码。
def generating_samples(input_data, target_data):
selected_rows = np.random.choice(len(input_data), 303)
replacing_rows = np.random.choice(selected_rows,203)
selected_columns = np.random.choice(3,13,1)
sample_data = input_data[selected_rows[:,None],selected_columns]
target_of_sample_data = target_data[selected_rows]
#replicating data
replicated_sample_data = sample_data[replacing_rows]
target_of_replicated_sample_data = target_data[replacing_rows]
#concatenating data
sampled_input_data = np.vstack(sample_data, replicated_sample_data)
target_of_sample_data = target_of_sample_data.reshape(-1,1)
target_of_replicated_sample_data = target_of_replicated_sample_data.reshape(-1,1)
sampled_target_data = np.vstack(target_of_sample_data,target_of_replicated_sample_data)
return sampled_input_data , sampled_target_data, selected_rows,selected_columns
def grader_samples(a,b,c,d):
length = (len(a)==506 and len(b)==506)
sampled = (len(a)-len(set([str(i) for i in a]))==203)
rows_length = (len(c)==303)
column_length= (len(d)>=3)
assert(length and sampled and rows_length and column_length)
return True
a,b,c,d = generating_samples(x, y)
grader_samples(a,b,c,d)
但是正在发生以下错误。
IndexError Traceback (most recent call last)
<ipython-input-14-ca772632e834> in <module>
7 return True
8
----> 9 a,b,c,d = generating_samples(x, y)
10 grader_samples(a,b,c,d)
<ipython-input-13-bcf904f160e5> in generating_samples(input_data, target_data)
13
14 #replicating data
---> 15 replicated_sample_data = sample_data[replacing_rows]
16 target_of_replicated_sample_data = target_data[replacing_rows]
17
IndexError: index 391 is out of bounds for axis 0 with size 303
使用：replicated_sample_data = input_data[replacing_rows]，因为复制的样本数据来自原始数据集。并且样本数据已经从原始数据集中进行了采样，因此它是我们原始数据集的一个子集，并导致索引错误