getting ValueError : "Can only tuple-index with a MultiIndex "

Question

我正在尝试实现一个简单的 RNN 来预测整数序列中的下一个整数。所以，我有一个数据集如下：

Id  Sequence
1   1,0,0,2,24,552,21280,103760,70299264,5792853248,587159944704
2   1,1,5,11,35,93,269,747,2115,5933,16717,47003,132291,372157,1047181,2946251,8289731,23323853,65624397,184640891,519507267,1461688413,4112616845,11571284395,32557042499,91602704493,257733967693
4   0,1,101,2,15,102,73,3,40,16,47,103,51,74,116,4,57,41,125,17,12,48,9,104,30,52,141,75,107,117,69,5,148,58,88,42,33,126,152,18,160,13,38,49,55,10,28,105,146,31,158
5   1,4,14,23,42,33,35,34,63,66,87,116,84,101,126,164,128,102,135,143,149,155,203,224,186,204,210,237,261,218,219,286,257,266,361,355,336,302,374,339,371,398,340,409,348,388,494,436,407,406
6   1,1,2,5,4,2,6,13,11,4,10,10,12,6,8,29,16,11,18,20,12,10,22,26,29,12,38,30,28,8,30,61,20,16,24,55,36,18,24,52,40,12,42,50,44,22,46,58,55,29,32,60,52,38,40,78,36,28,58,40,60,30,66,125,48,20,66,80,44,24
9   0,31,59,90,120,151,181,212,243,273,304,334,365,396,424,455,485,516,546,577,608,638,669,699,730,761,789,820,850,881,911,942,973,1003,1034,1064,1095,1126,1155,1186,1216,1247,1277,1308,1339,1369,1400,1430
10  1,1,2,5,13,36,111,347,1134,3832,13126,46281,165283,598401,2202404,8168642,30653724,116082962,442503542,1701654889,6580937039,25603715395,100223117080,394001755683,1556876401398,6178202068457,24608353860698,98421159688268,394901524823138,1589722790850089
12  0,0,0,0,112,40286,5485032,534844548,45066853496,3538771308282,267882021563464,19861835713621616,1453175611052688600,105278656040052332838,7564280930105061931496

到目前为止我的代码是：

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import math
from keras.models import Sequential
from keras.layers import Dense
from keras.layers import SimpleRNN
from sklearn.preprocessing import MinMaxScaler
from sklearn.metrics import mean_squared_error
from keras.preprocessing.sequence import pad_sequences

def stoarray(data = [], sep = ','):
    return data.map(lambda x: np.array(x.split(sep), dtype=float))

def create_dataset(dataset, window_size=1):
    dataX, dataY = [], []
    for i in range(len(dataset)-window_size-1):
        a = dataset[i:(i+window_size), 0]
        dataX.append(a)
        dataY.append(dataset[i + window_size, 0]) #gives the ValueError : Can only tuple index with multi index
    return np.array(dataX), np.array(dataY)

# fix random seed for reproducibility
np.random.seed(7)

# loading data
colna = ['id', 'seq']
train_data = pd.read_csv('G:/Python/integer_sequencing/testfile.csv', header=1)
train_data.columns = colna
dataset = train_data['seq']
#print(dataset)
window_size = 1
X_train, Y_train = create_dataset(dataset, window_size)

print(X_train.head(5))
print(Y_train.head(5))

我正在尝试将每个序列拆分为 X_train 作为包含除最后一项之外的完整集合的输入，并且 Y_train 被视为仅包含最后一位数字的输出。但是当我运行代码时，我得到了 ValueError：只能使用 MultiIndex 进行元组索引。任何人都可以解释它对我的代码意味着什么以及我必须做什么才能解决它。

回溯调用：

PS - 我是堆栈溢出和深度学习的新手，所以如果你能建议并帮助我格式化我的问题，我将不胜感激。

Answer 1

dataset[i:(i+window_size), 0] 中的 i:(i+window_size), 0 有问题。

在您的代码中 dataset 表示 train_data['seq'] 是单列 - 一维 Series - 但您使用 i:(i+window_size), 0 就像在二维 DataFrame.

您只能使用单个整数，例如 dataset[0] 或切片 dataset[i:(i+window_size)]

getting ValueError : "Can only tuple-index with a MultiIndex "

getting ValueError : "Can only tuple-index with a MultiIndex "

python

deep-learning

keras

rnn