Update README.md

README.md

@@ -3,6 +3,7 @@ python 3.9.7
 ![dann](/make_moons_experiemnt_dann.png) ![without_adapt](/make_moons_experiment_withoutadapt.png)
 ## algo/
 implementations of domain invariant learning algo.
+--algo_name can switch them.
 |file name|note|
 |---|---|
 |algo.py|DANN algo https://arxiv.org/pdf/1505.07818|
@@ -15,6 +16,9 @@ implementations of experiment workflow (data load, preprocess, init NN, training
 |make_moons|https://scikit-learn.org/stable/modules/generated/sklearn.datasets.make_moons.html|`python -m domain-invariant-learning.experiments.make_moons.experiment`|
 |ecodataset|https://vs.inf.ethz.ch/res/show.html?what=eco-data|`git clone https://github.com/oh-yu/deep_occupancy_detection/tree/feature/JSAI`<br>`run all cells of 01.ipynb - 05.ipynb`<br>`python -m domain-invariant-learning.experiments.ecodataset_synthetic.experiment`|
 |ecodataset_synthetic|see experiment.py logic|`git clone https://github.com/oh-yu/deep_occupancy_detection/tree/feature/JSAI`<br>`run all cells of 01.ipynb - 05.ipynb`<br>`python -m domain-invariant-learning.experiments.ecodataset_synthetic.experiment`|
+|HHAR|https://archive.ics.uci.edu/dataset/344/heterogeneity+activity+recognition|`download data`<br>`python -m domain-invariant-learning.experiments.HHAR.experiment`|
+|MNIST|https://github.com/mashaan14/MNIST-M/tree/main|`download data`<br>`python -m domain-invariant-learning.experiments.MNIST.experiment`|
+
 ## networks/
 implementations of networks which include layers, fit method, predict method, predict_proba method.
 Domain Invariant Laerning and Without Adapt and Train on Target related free params should be set here.