{"id":17293390,"url":"https://github.com/xuyxu/deep-clustering-network","last_synced_at":"2025-04-14T11:07:15.299Z","repository":{"id":44325538,"uuid":"291179533","full_name":"xuyxu/Deep-Clustering-Network","owner":"xuyxu","description":"PyTorch Implementation of \"Towards K-Means-Friendly Spaces: Simultaneous Deep Learning and Clustering,\" Bo Yang et al., ICML'2017.","archived":false,"fork":false,"pushed_at":"2021-01-15T12:37:49.000Z","size":112,"stargazers_count":128,"open_issues_count":1,"forks_count":31,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-04-14T11:07:10.772Z","etag":null,"topics":["clustering","deep-learning","pytorch"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/xuyxu.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2020-08-29T01:37:26.000Z","updated_at":"2025-04-03T08:05:14.000Z","dependencies_parsed_at":"2022-09-05T06:21:12.129Z","dependency_job_id":null,"html_url":"https://github.com/xuyxu/Deep-Clustering-Network","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/xuyxu%2FDeep-Clustering-Network","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/xuyxu%2FDeep-Clustering-Network/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/xuyxu%2FDeep-Clustering-Network/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/xuyxu%2FDeep-Clustering-Network/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/xuyxu","download_url":"https://codeload.github.com/xuyxu/Deep-Clustering-Network/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248868766,"owners_count":21174758,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["clustering","deep-learning","pytorch"],"created_at":"2024-10-15T10:48:00.589Z","updated_at":"2025-04-14T11:07:15.276Z","avatar_url":"https://github.com/xuyxu.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"### DCN: Deep Clustering Network\nI found the official implementation of deep clustering network (DCN) is outdated (https://github.com/boyangumn/DCN-New). This repo is a re-implementation of DCN using PyTorch.\n\n#### Introduction\nAn interesting work that jointly performs unsupervised dimension reduction and clustering using a neural network autoencoder.\n\n#### How to run\nHere I offer a demo on training DCN on the MNIST dataset (corresponding to Section 5.2.5 in the raw paper). To run this demo, simply type the following command:\n\n```\npython mnist.py\n```\n\n#### Acknowledgement\nFor anyone with interests, you can also refer to the implementation of Günther Eder: https://github.com/guenthereder/Deep-Clustering-Network, which has more details on the reproducibility.\n\n#### Experiment\nI trained the DCN model on MNIST dataset, hyper-parameters like network structure were set as values reported in the paper. The left figure presents the reconstruction error of the autoencoder during the pre-training stage, and the right figure presents changes on NMI and ARI (two metrics employed in the paper) during the training stage. The best NMI result I have got is around 0.65.\n\n![MNIST Experiment Result](./mnist_exp.png)\n\n#### Package dependency\n* scikit-lean==0.23.1\n* pytorch==1.6.0\n* torchvision==0.7.0\n* joblib==0.16.0\n\nIn my practice, this implementation also works fine on PyTorch 0.4.1. Feel free to open an issue if there were incompatibility problems.\n\n#### Reference\n* Yang et al. ''Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering'', ICML-2017 (https://arxiv.org/pdf/1610.04794.pdf)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fxuyxu%2Fdeep-clustering-network","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fxuyxu%2Fdeep-clustering-network","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fxuyxu%2Fdeep-clustering-network/lists"}