We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
我发现如果instruments中只填几只股票,例如随便选择的["SH600006", "SH600007"]
Training until validation scores don't improve for 50 rounds [20] train's l2: 0.497512 valid's l2: 0.5 [40] train's l2: 0.497512 valid's l2: 0.5 Early stopping, best iteration is: [1] train's l2: 0.497512 valid's l2: 0.5
然后用这个模型预测的话 pred_scores = model.predict(dataset)
datetime instrument score 2018-12-03 SH600006 0.0 SH600007 0.0
我也使用了optuna 进行搜参,但是一直没有找到可用的参数组合
是我的使用方式有问题吗?
The text was updated successfully, but these errors were encountered:
看这个预测结果,模型没有学到东西,输出的分数都是一样的。也可能是你数据没有很好的做特征处理,机器学习比较依赖特征工程。
Sorry, something went wrong.
No branches or pull requests
❓ Questions and Help
我发现如果instruments中只填几只股票,例如随便选择的["SH600006", "SH600007"]
Training until validation scores don't improve for 50 rounds
[20] train's l2: 0.497512 valid's l2: 0.5
[40] train's l2: 0.497512 valid's l2: 0.5
Early stopping, best iteration is:
[1] train's l2: 0.497512 valid's l2: 0.5
然后用这个模型预测的话
pred_scores = model.predict(dataset)
我也使用了optuna 进行搜参,但是一直没有找到可用的参数组合
是我的使用方式有问题吗?
The text was updated successfully, but these errors were encountered: