python-3.x - ValueError : Expected 2D array, 得到的是一维数组。 Python 线性回归函数

Question

我不知道如何解决此错误消息。我希望有人能帮帮忙。谢谢。

import numpy as np
from sklearn import linear_model
from sklearn.model_selection import train_test_split


def desired_marketing_expenditure(x_train_marketing_expenditure, y_train_units_sold, x_test_units_sold):

    X_train, X_test, y_train, y_test = train_test_split(x_train_marketing_expenditure, y_train_units_sold, test_size=0.4, random_state=101)
    lm = linear_model.LinearRegression()
    lm.fit(X_train,y_train)
    print(lm.intercept_)
    print(lm.coef_)

    #predictions = lm.predict(x_test_units_sold)

print(desired_marketing_expenditure([300000, 200000, 400000, 300000, 100000],[60000, 50000, 90000, 80000, 30000],60000))

OUT:ValueError: 需要 2D 数组，却得到 1D 数组: 数组=[400000 200000 300000]。 如果数据具有单个特征，则使用 array.reshape(-1, 1) reshape 数据；如果数据包含单个样本，则使用 array.reshape(1, -1) reshape 数据。

Answer 1

尝试将您的 X_train reshape 为错误中提到的 (-1,1)

import numpy as np
from numpy import array
from sklearn import linear_model
from sklearn.model_selection import train_test_split


def desired_marketing_expenditure(x_train_marketing_expenditure, y_train_units_sold, x_test_units_sold):

    X_train, X_test, y_train, y_test = train_test_split(x_train_marketing_expenditure, y_train_units_sold, test_size=0.4, random_state=101)
    lm = LinearRegression()
    X_train=array(X_train).reshape(-1,1)
    lm.fit(X_train,y_train)
    print(lm.intercept_)
    print(lm.coef_)

    #predictions = lm.predict(x_test_units_sold)

print(desired_marketing_expenditure([300000, 200000, 400000, 300000, 100000],[60000, 50000, 90000, 80000, 30000],60000))

输出:

13333.333333333343
[0.2]
None