擅长:python、mysql、java
<p>使用<a href="https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LinearRegression.html" rel="nofollow noreferrer">Scikit-learn Linear Regression</a></p>
<p>下面是一个代码示例,我使用一个3次多项式执行线性回归,该多项式通过值为1和零导数的点0。您只需将create_vector函数与所需函数相适应。在</p>
<pre><code>from sklearn import linear_model
import numpy as np
def create_vector(x):
# currently representing a polynom Y = a*X^3 + b*X^2
x3 = np.power(x, 3)
x2 = np.power(x, 2)
X = np.append(x3, x2, axis=1)
return X
data_x = [some_data_input]
data_y = [some_data_output]
x = np.array(data_x).reshape(-1, 1)
y_data = np.array(data_y).reshape(-1, 1)-1 # -1 to pass by the point (0,1)
X = create_vector(x)
regr = linear_model.LinearRegression(fit_intercept=False)
regr.fit(X, y_data)
</code></pre>