FAQ: Linear Regression - Review


#1

This community-built FAQ covers the “Review” exercise from the lesson “Linear Regression”.

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Data Science

Machine Learning

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#2
import codecademylib3_seaborn
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.linear_model import LinearRegression
from sklearn.datasets import load_boston

# Boston housing dataset
boston = load_boston()

df = pd.DataFrame(boston.data, columns = boston.feature_names)

# Set the x-values to the nitrogen oxide concentration:
X = df[['NOX']]
# Y-values are the prices:
y = boston.target

# Can we do linear regression on this?




plt.scatter(X, y, alpha=0.4)
# Plot line here:

plt.title("Boston Housing Dataset")
plt.xlabel("Nitric Oxides Concentration")
plt.ylabel("House Price ($)")
plt.show()
line_fitter = LinearRegression()
y_predicted = line_fitter.predict(X)
plt.plot(X,y_predicted)
plt.show()

Can anyone tell me why my linear regression line doesn’t show up in the graph? I am really confused.


#3

Hi eleseeu,

The line line_fitter.fit(X,y) is missing before the call to the method .predict().