【深度学习基础-11】简单线性回归（下）--实例及python代码实现

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比如有5组数据，让你去做简单线性回归。 

python代码实现上述过程

import numpy as np

def fitSLR(x,y):
    n = len(x)
    dinominator = 0
    numerator = 0
    for i in range(0, n):
        numerator += (x[i] - np.mean(x))*(y[i] - np.mean(y))
        dinominator += (x[i] - np.mean(x))**2

    print("numerator", numerator)
    print("dinominator", dinominator)
    b1 = numerator/float(dinominator)
    b0 = np.mean(y)/float(np.mean(x))

    return b0, b1

def predict(x, b0, b1):
    return b0 + x*b1

x = [1, 3, 2, 1, 3]
y = [14, 24, 18, 17, 27]

b0, b1 = fitSLR(x, y)

print("intercept:", b0 , "  slope:", b1)

x_test = 6

y_test = predict(6, b0, b1)

print("y_test: ", y_test)

运行结果如下