sklearn问题:进行回归时发现样本数量不一致的数组

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问题描述

这个问题似乎以前曾被问过，但我似乎无法发表评论以进一步澄清已接受的答案，而且我也无法弄清楚所提供的解决方案.

this question seems to have been asked before, but I can't seem to comment for further clarification on the accepted answer and I couldn't figure out the solution provided.

我正在尝试学习如何对自己的数据使用sklearn.基本上，我得到了过去100年中两个不同国家/地区的GDP年度变化百分比.我现在只是想学习使用单个变量.我本质上想做的是使用sklearn来预测给定B国GDP的百分比变化后，A国GDP的百分比变化.

I am trying to learn how to use sklearn with my own data. I essentially just got the annual % change in GDP for 2 different countries over the past 100 years. I am just trying to learn using a single variable for now. What I am essentially trying to do is use sklearn to predict what the GDP % change for country A will be given the percentage change in country B's GDP.

问题是我收到一条错误消息:

The problem is that I receive an error saying:

这是我的代码:

import sklearn.linear_model as lm
import numpy as np
import scipy.stats as st
import matplotlib.pyplot as plt
import matplotlib.dates as mdates


def bytespdate2num(fmt, encoding='utf-8'):#function to convert bytes to string for the dates.
    strconverter = mdates.strpdate2num(fmt)
    def bytesconverter(b):
        s = b.decode(encoding)
        return strconverter(s)
    return bytesconverter

dataCSV = open('combined_data.csv')

comb_data = []

for line in dataCSV:
    comb_data.append(line)

date, chngdpchange, ausgdpchange = np.loadtxt(comb_data, delimiter=',', unpack=True, converters={0: bytespdate2num('%d/%m/%Y')})


chntrain = chngdpchange[:-1]
chntest = chngdpchange[-1:]

austrain = ausgdpchange[:-1]
austest = ausgdpchange[-1:]

regr = lm.LinearRegression()
regr.fit(chntrain, austrain)

print('Coefficients: \n', regr.coef_)

print("Residual sum of squares: %.2f"
      % np.mean((regr.predict(chntest) - austest) ** 2))

print('Variance score: %.2f' % regr.score(chntest, austest))

plt.scatter(chntest, austest,  color='black')
plt.plot(chntest, regr.predict(chntest), color='blue')

plt.xticks(())
plt.yticks(())

plt.show()

我做错了什么?我本质上试图将sklearn教程(他们使用了一些糖尿病数据集)应用于我自己的简单数据.我的数据仅包含日期，A国在特定年份的GDP百分比变化以及B国在同一年的GDP百分比变化.

What am I doing wrong? I essentially tried to apply the sklearn tutorial (They used some diabetes data set) to my own simple data. My data just contains the date, country A's % change in GDP for that specific year, and country B's % change in GDP for that same year.

我在>此处尝试了解决方案和此处(主要是试图在第一个链接中找到有关该解决方案的更多信息)，但只会收到完全相同的错误.

I tried the solutions here and here (basically trying to find more out about the solution in the first link), but just receive the exact same error.

以下是完整的回溯，以备您查看:

Here is the full traceback in case you want to see it:

Traceback (most recent call last):
  File "D:\My Stuff\Dropbox\Python\Python projects\test regression\tester.py", line 34, in <module>
    regr.fit(chntrain, austrain)
  File "D:\Programs\Installed\Python34\lib\site-packages\sklearn\linear_model\base.py", line 376, in fit
    y_numeric=True, multi_output=True)
  File "D:\Programs\Installed\Python34\lib\site-packages\sklearn\utils\validation.py", line 454, in check_X_y
    check_consistent_length(X, y)
  File "D:\Programs\Installed\Python34\lib\site-packages\sklearn\utils\validation.py", line 174, in check_consistent_length
    "%s" % str(uniques))
ValueError: Found arrays with inconsistent numbers of samples: [  1 107]

the

sklearn问题:进行回归时发现样本数量不一致的数组

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