From 5d4dba2f7f57aab3e009b3787e1da2d6309c1197 Mon Sep 17 00:00:00 2001 From: MogicianXD <38429957+MogicianXD@users.noreply.github.com> Date: Fri, 10 Nov 2023 12:35:12 +0800 Subject: [PATCH] Update README.md --- examples/benchmarks_dynamic/incremental/README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/examples/benchmarks_dynamic/incremental/README.md b/examples/benchmarks_dynamic/incremental/README.md index dafe4090e1..a4870196f8 100644 --- a/examples/benchmarks_dynamic/incremental/README.md +++ b/examples/benchmarks_dynamic/incremental/README.md @@ -5,7 +5,7 @@ This is the official implementation of `DoubleAdapt`, an incremental learning fr The paper has been accepted by KDD 2023, which is better to read in [[arXiv](https://arxiv.org/abs/2306.09862)]. -To get rid of dependencies on qlib, please refer to our [API](https://github.com/SJTU-Quant/DoubleAdapt) repo. +To get rid of dependencies on qlib, please refer to our [API](https://github.com/SJTU-Quant/DoubleAdapt) repo. (This API repo is not well maintained and may have undiscovered bugs. We still recommend our qlib repo) ## :newspaper: News Sep 15, 2023 :hammer: Support overriding learning rates during online training (meta-valid and meta-test). @@ -15,9 +15,9 @@ We also **CHANGED** our argparser: the arg `--lr` now means the learning rate of ## Organization The runner program is [./main.py](main.py). -The core implementation of the framework lies in [qlib/contrib/meta/incremental/](https://github.com/SJTU-Quant/qlib/contrib/meta/incremental/). +The core implementation of the framework lies in [qlib/contrib/meta/incremental/](https://github.com/SJTU-Quant/qlib/blob/main/qlib/contrib/meta/incremental/). -The implementation of any forecast model lies in [qlib/contrib/model/](https://github.com/SJTU-Quant/qlib/contrib/model/) (e.g., GRU is in [qlib/contrib/model/pytorch_gru.py](https://github.com/SJTU-Quant/qlib/contrib/model/pytorch_gru.py)). +The implementation of any forecast model lies in [qlib/contrib/model/](https://github.com/SJTU-Quant/qlib/blob/main/qlib/contrib/model/) (e.g., GRU is in [qlib/contrib/model/pytorch_gru.py](https://github.com/SJTU-Quant/qlib/blob/main/qlib/contrib/model/pytorch_gru.py)). ## Scripts ```bash