c*u 发帖数: 916 | 1 我有一组实验数据,理论上应当符合以下规律:
y = y_high, if x > thr
y = y_low, if x < thr
y_high, y_low, thr 是未知的常数,thr是所需要得到的东西.好像3D bruteforce
search 寻找最低点不是很有效率.
举个通俗的例子,假设x是温度,y是水的体积,那么Thr是熔点.但是实验数据中
y的测量有很大noise, 所以必须拟合.
谢谢, | A*******r 发帖数: 768 | 2 神经网络
【在 c*u 的大作中提到】 : 我有一组实验数据,理论上应当符合以下规律: : y = y_high, if x > thr : y = y_low, if x < thr : y_high, y_low, thr 是未知的常数,thr是所需要得到的东西.好像3D bruteforce : search 寻找最低点不是很有效率. : 举个通俗的例子,假设x是温度,y是水的体积,那么Thr是熔点.但是实验数据中 : y的测量有很大noise, 所以必须拟合. : 谢谢,
| c*u 发帖数: 916 | 3 ai.. unfortunately i have no idea how to build neural network.
I just did a try. It looks like iteration works pretty well. Just need make
a guess of y_high and y_low, find the best thr. Then set y_high, y_low as
the mean values for xthr. Repeat the iterations until converge.
Only takes 2-5 iterations to converge. Calculation time is O(n) instead of
O(n^3). For the data, it seems the fitting rarely stuck in local maxima.
Sorry for the dumb question.
【在 A*******r 的大作中提到】 : 神经网络
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