BuildingMachineLearningSystemsWithPython/ch07/figure4.py at master · BobPyron/BuildingMachineLearningSystemsWithPython

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# This code is supporting material for the book

# Building Machine Learning Systems with Python

# by Willi Richert and Luis Pedro Coelho

# published by PACKT Publishing

# It is made available under the MIT License

from sklearn.linear_model import Lasso

import numpy as np

from sklearn.datasets import load_boston

import pylab as plt

from mpltools import style

style.use('ggplot')

boston = load_boston()

plt.scatter(boston.data[:, 5], boston.target)

plt.xlabel("RM")

plt.ylabel("House Price")

x = boston.data[:, 5]

xmin = x.min()

xmax = x.max()

x = np.array([[v, 1] for v in x])

y = boston.target

(slope, bias), res, _, _ = np.linalg.lstsq(x, y)

plt.plot([xmin, xmax], [slope * xmin + bias, slope * xmax + bias], ':', lw=4)

las = Lasso()

las.fit(x, y)

y0 = las.predict([xmin, 1])

y1 = las.predict([xmax, 1])

plt.plot([xmin, xmax], [y0, y1], '-', lw=4)

plt.savefig('Figure3.png', dpi=150)