Comments (1)
你好,这样做是可以的,除模型之外,还需要在训练数据的生成上也做改变,相关代码都已经更新在GitHub中了。
但是这样做的预测效果并不比之前好,个人觉得可能的原因:目前是按照batch_size = 1,也即一个一个样本训练的,这样才能让上一个样本的final_state作为下一次的init_state。但这样训练batch太小,容易过拟合。
当然,在预测的时候是把上一次的final_state作为下一次的init_state,预测结果有提升。
from stock_predict_with_lstm.
Related Issues (11)
- 请问如何获取预测后的数据 HOT 2
- question about do_continue_train
- 时间特征为什么没有考虑 HOT 2
- 你好,输出图我看不太懂 HOT 1
- do_train_visualized = False HOT 3
- 请教关于训练和预测时的数据格式的问题
- 您好,代码运行后有个问题想请教您 HOT 1
- dropout并没有使用 HOT 1
- The codes are aimed at Singlevariate time-series or Multivariate time-series? HOT 1
- 会不会有未来函数呢 HOT 1
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from stock_predict_with_lstm.