我正在学习一门关于EdX的课程,内容是在数据科学中使用Python编程。当使用给定的函数来绘制我的线性回归模型的结果时,该图看起来非常不稳定,所有的散点都聚集在底部,而回归线则在顶部。
我不确定是定义的函数drawLine
不正确,还是我的建模过程中有其他问题。
下面是已定义的函数
def drawLine(model, X_test, y_test, title, R2):
fig = plt.figure()
ax = fig.add_subplot(111)
ax.scatter(X_test, y_test, c='g', marker='o')
ax.plot(X_test, model.predict(X_test), color='orange', linewidth=1, alpha=0.7)
title += " R2: " + str(R2)
ax.set_title(title)
print(title)
print("Intercept(s): ", model.intercept_)
plt.show()
下面是我写的代码
import pandas as pd
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from sklearn import linear_model
from sklearn.model_selection import train_test_split
matplotlib.style.use('ggplot') # Look Pretty
# Reading in data
X = pd.read_csv('Datasets/College.csv', index_col=0)
# Wrangling data
X.Private = X.Private.map({'Yes':1, 'No':0})
# Splitting data
roomBoard = X[['Room.Board']]
accStudent = X[['Accept']]
X_train, X_test, y_train, y_test = train_test_split(roomBoard, accStudent, test_size=0.3, random_state=7)
# Training model
model = linear_model.LinearRegression()
model.fit(X_train, y_train)
score = model.score(X_test, y_test)
# Visualise results
drawLine(model, X_test, y_test, "Accept(Room&Board)", score)
我使用的数据可以在here中找到
谢谢您抽时间见我。
任何帮助或建议都是非常感谢的。
发布于 2018-05-31 22:53:06
在您的drawLine函数中,我将ax.scatter
更改为plt.scatter
。我还将roomBoard
和accStudent
改为numpy数组,而不是pandas.Series。最后,我将"private“列的更新方式更改为
X.loc[:, "Private"] = X.Private.map({'Yes':1, 'No':0})
Pandas docs解释了我为什么要做这样的更改。其他一些小的变化只是表面上的。
我让下面的代码正常工作:
import pandas as pd
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from sklearn import linear_model
from sklearn.model_selection import train_test_split
matplotlib.style.use('ggplot') # Look Pretty
# Reading in data
X = pd.read_csv('College.csv', index_col=0)
# Wrangling data
X.loc[:, "Private"] = X.Private.map({'Yes':1, 'No':0})
# Splitting data
roomBoard = X.loc[:, 'Room.Board'].values.reshape((len(X),1))
accStudent = X.loc[:, 'Accept'].values.reshape((len(X),1))
X_train, X_test, y_train, y_test = train_test_split(roomBoard, accStudent, test_size=0.3, random_state=7)
# Training model
model = linear_model.LinearRegression()
model.fit(X_train, y_train)
score = model.score(X_test, y_test)
# Visualise results
def drawLine(model, X_test, y_test, title, R2):
fig = plt.figure()
ax = fig.add_subplot(111)
plt.scatter(X_test, y_test, c='g', marker='o')
y_pred = model.predict(X_test)
plt.plot(X_test, y_pred, color='orange', linewidth=1, alpha=0.7)
title += " R2: " + str(R2)
ax.set_title(title)
print(title)
print("Intercept(s): ", model.intercept_)
plt.xticks(())
plt.yticks(())
plt.show()
drawLine(model, X_test, y_test, "Accept(Room&Board)", score)
https://stackoverflow.com/questions/50626539
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