ZigZag 这个序列根本就不需要预测，if you know the lag(ZigZag)=-1 ,then the ZigZag must be 1;the lag(ZigZag)=1 ,then the zigzag=-1;
all of the lag(ZigZag) is occured at the past time,it can predict the zigzag 100% accurately。so if you know the time is zigzag point ,you can 100% accurately
predict the zigzag is -1 or 1.
But in the realtime you cannot know the time is zigzag point,so you must caculate the third status (0)， so how can it work?
ZZ is really not defined on the last bars (the last vertex). But they do not need me. Neural network training is conducted on ZZ values without the last 300 bars !! On those bars where ZZ is defined.
You carefully look at the scripts and do not rush to conclusions. You can look stupid.
to Vladimir Perervenko: thanks again for those wonderful articles, you did and doing really good research! And I must apologize for this stupid thing from "freewalk", not all chinese like him.
绘制一个简单的绘图说明的数字（-1，1（0）????
请您仔细阅读的文章？而旁边呢？而且不知道如何使用ZZ？
也许翻译不好？
指定更精确您的意见，请能提高英语水平？
ZigZag 这个序列根本就不需要预测，if you know the lag(ZigZag)=-1 ,then the ZigZag must be 1;the lag(ZigZag)=1 ,then the zigzag=-1;
all of the lag(ZigZag) is occured at the past time,it can predict the zigzag 100% accurately。so if you know the time is zigzag point ,you can 100% accurately
predict the zigzag is -1 or 1.
But in the realtime you cannot know the time is zigzag point,so you must caculate the third status (0)， so how can it work?
You can reference this right articl https://www.mql5.com/zh/articles/2773.
好的
Good afternoon.
ZZ is really not defined on the last bars (the last vertex). But they do not need me. Neural network training is conducted on ZZ values without the last 300 bars !! On those bars where ZZ is defined.
You carefully look at the scripts and do not rush to conclusions. You can look stupid.
Good luck
in the realtime ,do you use 'without the last 300 bars '!?
You looks so stupid ,can you use it in the realtime.?
All of your article are wrong ,because your target define is wrong.All canot work in the realtime,
as follow your point ,you singal will happened after 300 bars later.
in the realtime ,do you use 'without the last 300 bars '!?
You looks so stupid ,can you use it in the realtime.?
All of your article are wrong ,because your target define is wrong.All canot work in the realtime,
as follow your point ,you singal will happened after 300 bars later.
你并不真正了解作者的设想，自己想象的过于幼稚了，说出的stupid只是映射在你自己身上而已，请不要再给国人丢脸，不但stupid，而且丑陋。
to Vladimir Perervenko: thanks again for those wonderful articles, you did and doing really good research! And I must apologize for this stupid thing from "freewalk", not all chinese like him.
我在下一个分支中回答了您的问题。
你好，弗拉基米尔、
我没有找到您对这个问题的答复。我也不确定 Dig 的值是多少，能否请您具体说明一下！
亲爱的各位、
谁能告诉我ZZ函数 变量 中定义的--Dig--是什么意思？如果是，这个常数的值应该是多少？
Dig - 引号中小数点后的位数。可能是 5 或 3。
很抱歉迟迟没有回复。没有看到问题。讨论分散在许多分支中。我没有时间跟踪。
请原谅。
文章内容丰富，感谢您的劳动。
不过，这一点值得商榷：
1. 使用分层方法，在每个条形图上标注选定的目标。将两个不具代表性的样本混合在一起通常会改善结果，从而使结果出现偏差。
2- 基于已构建模型的特征选择，尤其是考虑到第一次拆分随机和贪婪法，更像是模型构建方法的特征缩减法。贪婪法并不总是正确和稳定的。在这种情况下，也许你至少需要使用不同的子样本。
直到最后，我才明白第二种方法--是同样使用随机的第一个预测因子，然后我们尝试建立一个树叶，还是建立一棵树，留下最好的树叶，用于评估？