以前介绍过一个backtrader的参数优化包optunity,此包有个缺点,假设参数是列表[5,6],optunit会搜索5和6之间的小数,也就是它是连续搜索,而不是离散搜索,这导致很多无效搜索,因为我们实际只想搜索5和6这两个数。最近发现一个包可以执行离散搜索,那就是gradient_free_optimizers。以下案例内容来自扫地僧backtrader技术教...
Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces. - SimonBlanke/Gradient-Free-Optimizers
Noise-free, good quality (SNR>100) datasets were inverted usingLevenberg–Marquardt: LM (gradient) and Nelder–Mead: NM (gradient-free) methods. All simulations were performed using acoupled simulation-optimization model. Performance of the two optimizers is evaluated by comparing model predictions ...
在《扫地僧Backtrader给力教程系列一:量化回测核心篇 增订版》中,我们介绍了backtrader中一个执行大规模参数优化的包optunity,但它有个缺点,就是其内部对要优化的参数搜索的是连续浮点数,因此在策略里必须对参数取整,这实际上导致一些无效搜索,降低了性能。 好在还有一个包gradient-free-optimizers(安装方法:pip install...
【Gradient-Free-Optimizers A collection of modern optimization methods in Python】http://t.cn/A6tKZZzy Gradient-Free-Optimizers Python中现代优化方法的集合 。#网路冷眼技术分享[超话]#
D:...\gradient_free_optimizers\search.py in set_random_seed(nth_process, random_state) 33 34 if random_state is None: ---> 35 random_state = np.random.randint(0, high=2 ** 32 - 2) 36 37 random.seed(random_state + nth_process) mtrand.pyx in numpy.random.mtrand.RandomState.randi...