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README.md

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@@ -29,9 +29,9 @@ It supports a wide variety of structures like low-order structures (graph, direc
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In addition, DHG's [dhg.experiments](https://deephypergraph.readthedocs.io/en/latest/api/experiments.html) module (that implements **Auto-ML** upon [Optuna](https://optuna.org)) can help you automatically tune the hyper-parameters of your models in training and easily outperforms the state-of-the-art models.
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![Framework of DHG Structures](docs/source/_static/img/fw_dhg_structure.jpg)
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![Framework of DHG Structures](https://deephypergraph.com/fw_dhg_structure.jpg)
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![Framework of DHG Function Library](docs/source/_static/img/fw_dhg_other.jpg)
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![Framework of DHG Function Library](https://deephypergraph.com/fw_dhg_other.jpg)
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* [Hightlights](#highlights)
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* [Installation](#installation)
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You can draw the graph, hypergraph, directed graph, and bipartite graph with DHG's visualization tool. More details see the [Tutorial](https://deephypergraph.readthedocs.io/en/latest/tutorial/vis_structure.html)
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![Visualization of graph and hypergraph](docs/source/_static/img/readme_graph_hypergraph.png)
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![Visualization of graph and hypergraph](https://deephypergraph.com/readme_graph_hypergraph.png)
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```python
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import matplotlib.pyplot as plt
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plt.show()
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```
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![Visualization of directed graph and bipartite graph](docs/source/_static/img/readme_digraph_bigraph.png)
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![Visualization of directed graph and bipartite graph](https://deephypergraph.com/readme_digraph_bigraph.png)
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```python
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import matplotlib.pyplot as plt
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- **[News20](https://deephypergraph.readthedocs.io/en/latest/generated/dhg.data.News20.html#dhg.data.News20)**: A newspaper network dataset for vertex classification task.
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- **[DBLP8k](https://deephypergraph.readthedocs.io/en/latest/generated/dhg.data.DBLP8k.html#dhg.data.DBLP8k)**: The DBLP-8k dataset is a citation network dataset for link prediction task.
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## Metrics
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### Classification Metrics

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