Regresi linear

Dasar-Dasar Probabilitas di Python

Alexander A. Ramírez M.

CEO @ Synergy Vision

Fungsi linear

Plot fungsi linear

Plot fungsi linear

$$ y = \color{red}{slope}*x + \color{blue}{intercept} $$

Plot fungsi linear dengan gangguan acak

$$ y = slope*x + intercept + \color{red}{random\_number} $$

Plot jam belajar vs skor

Mencocokkan data dengan model konstan, linear, kuadratik, dan logaritmik

Apa kriteria untuk menentukan model terbaik?

Animasi plot model linear

Plot residual

Plot residual dan meminimalkan galat

Plot residual model linear

# Import LinearRegression
from sklearn.linear_model import LinearRegression

# sklearn linear model
model = LinearRegression()
model.fit(hours_of_study, scores)

# Get parameters
slope = model.coef_[0]
intercept = model.intercept_

# Print parameters
print(slope, intercept)

(1.496703900384545, 52.44845266434719)

# Score prediction
score = model.predict(np.array([[15]]))
print(score)

[74.89901117]

$$ $$

import matplotlib.pyplot as plt

plt.scatter(hours_of_study, scores)
plt.plot(hours_of_study_values, model.predict(hours_of_study_values))
plt.show()

Plot kecocokan model linear

Dasar-Dasar Probabilitas di Python