这篇文章主要介绍“Java线性回归基础代码怎么写”,在日常操作中,相信很多人在Java线性回归基础代码怎么写问题上存在疑惑,小编查阅了各式资料,整理出简单好用的操作方法,希望对大家解答”Java线性回归基础代码怎么写”的疑惑有所帮助!接下来,请跟着小编一起来学习吧!
让客户满意是我们工作的目标,不断超越客户的期望值来自于我们对这个行业的热爱。我们立志把好的技术通过有效、简单的方式提供给客户,将通过不懈努力成为客户在信息化领域值得信任、有价值的长期合作伙伴,公司提供的服务项目有:国际域名空间、网络空间、营销软件、网站建设、宿州网站维护、网站推广。# Use linear model to model this data. from sklearn.linear_model import LinearRegression import numpy as np lr=LinearRegression() lr.fit(pga.distance[:,np.newaxis],pga['accuracy']) # Another way is using pga[['distance']] theta0=lr.intercept_ theta1=lr.coef_ print(theta0) print(theta1) #calculating cost-function for each theta1 #计算平均累积误差 def cost(x,y,theta0,theta1): J=0 for i in range(len(x)): mse=(x[i]*theta1+theta0-y[i])**2 J+=mse return J/(2*len(x)) theta0=100 theta1s = np.linspace(-3,2,197) costs=[] for theta1 in theta1s: costs.append(cost(pga['distance'],pga['accuracy'],theta0,theta1)) plt.plot(theta1s,costs) plt.show() print(pga.distance) #调整theta def partial_cost_theta0(x,y,theta0,theta1): #我们的模型是线性拟合函数时:y=theta1*x + theta0,而不是sigmoid函数,当非线性时我们可以用sigmoid #直接多整个x series操作,省的一个一个计算,最终求sum 再平均 h=theta1*x+theta0 diff=(h-y) partial=diff.sum()/len(diff) return partial partial0=partial_cost_theta0(pga.distance,pga.accuracy,1,1) def partial_cost_theta1(x,y,theta0,theta1): #我们的模型是线性拟合函数:y=theta1*x + theta0,而不是sigmoid函数,当非线性时我们可以用sigmoid h=theta1*x+theta0 diff=(h-y)*x partial=diff.sum()/len(diff) return partial partial1=partial_cost_theta1(pga.distance,pga.accuracy,0,5) print(partial0) print(partial1) def gradient_descent(x,y,alpha=0.1,theta0=0,theta1=0): #设置默认参数 #计算成本 #调整权值 #计算错误代价,判断是否收敛或者达到大迭代次数 most_iterations=1000 convergence_thres=0.000001 c=cost(x,y,theta0,theta1) costs=[c] cost_pre=c+convergence_thres+1.0 counter=0 while( (np.abs(c-cost_pre)>convergence_thres) & (counter数据集 :
复制下面数据,保存为: pga.csv
distance,accuracy 290.3,59.5 302.1,54.7 287.1,62.4 282.7,65.4 299.1,52.8 300.2,51.1 300.9,58.3 279.5,73.9 287.8,67.6 284.7,67.2 296.7,60 283.3,59.4 284,72.2 292,62.1 282.6,66.5 287.9,60.9 279.2,67.3 291.7,64.8 289.9,58.1 289.8,61.7 298.8,56.4 280.8,60.5 294.9,57.5 287.5,61.8 282.7,56 277.7,72.5 270.5,71.7 285.2,66 315.1,55.2 281.9,67.6 293.3,58.2 286,59.9 285.6,58.2 289.9,65.7 277.5,59 293.6,56.8 301.1,65.4 300.8,63.4 287.4,67.3 281.8,72.6 277.4,63.1 279.1,66.5 287.4,66.4 280.9,62.3 287.8,57.2 261.4,69.2 272.6,69.4 291.3,65.3 294.2,52.8 285.5,49 287.9,61.1 282.2,65.6 301.3,58.2 276.2,61.7 281.6,68.1 275.5,61.2 309.7,53.1 287.7,56.4 291.6,56.9 284.1,65 299.6,57.5 282.7,60 271.5,72 292.1,58.2 295,59.4 274.9,69 273.6,68.7 299.9,60.1 279.9,74 289.9,66 283.6,59.8 310.3,52.4 291.7,65.6 284.2,63.2 295,53.5 298.6,55.1 297.4,60.4 299.7,67.7 284.4,69.7 286.4,72.4 285.9,66.9 297.6,54.3 272.5,62 277,66.2 287.6,60.9 280.4,69.4 280,63.7 295.4,52.8 274.4,68.8 286.5,73.1 287.7,65.2 291.5,65.9 279,69.4 299,65.2 290.1,69.1 288.9,67.9 288.8,68.2 283.2,61 293.2,58.4 285.3,67.3 284.1,65.7 281.4,67.7 286.1,61.4 284.9,62.3 284.8,68.1 296,62 282.9,71.8 280.9,67.8 291.2,62 292.8,62.2 291,61.9 285.7,62.4 283.9,62.9 298.4,61.5 285.1,65.3 286.1,60.1 283.1,65.4 289.4,58.3 284.6,70.7 296.6,62.3 295.9,64.9 295.2,62.8 293.9,54.5 275,65.5 286.8,69.5 291.1,64.4 284.8,62.5 283.7,59.5 295.4,66.9 291.8,62.7 274.9,72.3 302.9,61.2 272.1,80.4 274.9,74.9 296.3,59.4 286.2,58.8 294.2,63.3 284.1,66.5 299.2,62.4 275.4,71 273.2,70.9 281.6,65.9 295.7,55.3 287.1,56.8 287.7,66.9 296.7,53.7 282.2,64.2 291.7,65.6 281.6,73.4 311,56.2 278.6,64.7 288,65.7 276.7,72.1 292,62 286.4,69.9 292.7,65.7 294.2,62.9 278.6,59.6 283.1,69.2 284.1,66 278.6,73.6 291.1,60.4 294.6,59.4 274.3,70.5 274,57.1 283.8,62.7 272.7,66.9 303.2,58.3 282,70.4 281.9,61 287,59.9 293.5,63.8 283.6,56.3 296.9,55.3 290.9,58.2 303,58.1 292.8,61.1 281.1,65 293,61.1 284,66.5 279.8,66.7 292.9,65.4 284,66.9 282,64.5 280.6,64 287.7,63.4 287.7,63.4 298.3,59.5 299.6,53.4 291.3,62.5 295.2,61.4 288,62.4 297.8,59.5 286,62.6 285.3,66.2 286.9,63.4 275.1,73.7到此,关于“Java线性回归基础代码怎么写”的学习就结束了,希望能够解决大家的疑惑。理论与实践的搭配能更好的帮助大家学习,快去试试吧!若想继续学习更多相关知识,请继续关注创新互联-成都网站建设公司网站,小编会继续努力为大家带来更多实用的文章!
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