在Numpy中獲取多項式迴歸統計

Question

我期待在Numpy中使用多項式迴歸（polyfit）獲得係數和截距，但不知道如何編寫腳本以獲得多項式函數。

我已代碼線性迴歸的代碼，這是我在下面附：

import matplotlib.pyplot as plt 
import sys 
from numpy import * 
import numpy as np 
import numpy.polynomial.polynomial as poly 
import pylab 
from scipy import stats 
from scipy.interpolate import * 
from datetime import datetime, timedelta 

#Open dataset1,dataset2 data 

data1 = np.loadtxt('/home/script/2_columns', delimiter=',', skiprows=0) 

data2 = np.loadtxt('/home/script/2_columns_a', delimiter=',', skiprows=0) 

#Define first column as dataset1 

#Define second column as dataset2 

x = data1[:,0] 
y = data1[:,1] 

#The stuff... 
slope, intercept, r_value, p_value, std_err = stats.linregress(x,y) 

Answer 1

你所需要的統計數據？如果沒有，你只需要係數，它真的很簡單使用numpy.polyfit：

import numpy as np 

# from your code 
data1 = np.loadtxt('/home/script/2_columns', delimiter=',', skiprows=0) 

x = data1[:,0] 
y = data1[:,1] 

degree = 3 
coeffs = np.polyfit(x, y, degree) 

# now, coeffs is an array which contains the polynomial coefficients 
# in ascending order, i.e. x^0, x^1, x^2 
intercept, linear, quadratic, cubic = coeffs 

如果您確實需要其他值，請註明您所需要的，因爲例如r_value是x之間的相關係數y，如果您不希望數據是線性的，這並不是非常有用。