使用高斯函数进行散点拟合预测

首先需要安装pyGPs包

    test = np.arange(0, 2800, 1)
    x = x_train # x_train,y_train为np.array()数组
    y = y_train 

    model = pyGPs.GPR() # specify model (GP regression)
    model.getPosterior(x, y) # fit default model (mean zero & rbf kernel) with data
    model.optimize(x, y) # optimize hyperparamters (default optimizer: single run minimize)
    yvals=model.predict(test) # predict test cases
    print(yvals)
    model.plot()