segmented-regression

Discontinuous segmented linear regression

Model finds split points by greedy minimization of total variance. Linear trend is eliminated while variance is calculated. Model require numpy and bottleneck for fast computations.

Examples

x = np.linspace(0., 5e8, 100000)
y = 1. - 1e-8*x
y[30000:] += 1.5
y[60000:] += 1.5
y[90000:] += 1.5
y += np.random.normal(scale=0.1, size=y.shape)

m = SegmentedRegression()
m.fit(x, y)
y_ = m.predict(x)
plt.plot(x, y, '.', alpha=.5, color='#999999')
plt.plot(x, y_, color='k')

x = np.linspace(0., np.pi, 100000)
y = np.sin(x)

m = SegmentedRegression(eps=1e-4)
m.fit(x, y)
y_ = m.predict(x)
plt.plot(x, y, '.', alpha=.5, color='#999999')
plt.plot(x, y_, color='k')