{"id":28976875,"url":"https://github.com/marta-barea/mlp-sonar-classifier","last_synced_at":"2025-09-18T00:34:30.633Z","repository":{"id":298118452,"uuid":"998923003","full_name":"Marta-Barea/mlp-sonar-classifier","owner":"Marta-Barea","description":"A simple project to train and evaluate two multilayer perceptron models on the Sonar data using TensorFlow, SciKeras, and Scikit-Learn — one without data standardization and another with standardized input data.","archived":false,"fork":false,"pushed_at":"2025-06-09T13:23:12.000Z","size":138,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-06-09T14:29:11.684Z","etag":null,"topics":["classification-algorithm","deep-learning","multilayer-perceptron","python","sonar-dataset"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Marta-Barea.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-06-09T13:18:13.000Z","updated_at":"2025-06-09T13:24:50.000Z","dependencies_parsed_at":"2025-06-09T14:32:09.596Z","dependency_job_id":"bc46fe39-645c-4324-8811-dc15daeb99d6","html_url":"https://github.com/Marta-Barea/mlp-sonar-classifier","commit_stats":null,"previous_names":["marta-barea/mlp-sonar-classifier"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Marta-Barea/mlp-sonar-classifier","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Marta-Barea%2Fmlp-sonar-classifier","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Marta-Barea%2Fmlp-sonar-classifier/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Marta-Barea%2Fmlp-sonar-classifier/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Marta-Barea%2Fmlp-sonar-classifier/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Marta-Barea","download_url":"https://codeload.github.com/Marta-Barea/mlp-sonar-classifier/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Marta-Barea%2Fmlp-sonar-classifier/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":261691328,"owners_count":23195051,"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":["classification-algorithm","deep-learning","multilayer-perceptron","python","sonar-dataset"],"created_at":"2025-06-24T14:10:41.634Z","updated_at":"2025-09-18T00:34:25.544Z","avatar_url":"https://github.com/Marta-Barea.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# MLP Sonar Classifier\n\nA simple project to train and evaluate two multilayer perceptron models on the Sonar data using TensorFlow, SciKeras, and Scikit-Learn — one without data standardization and another with standardized input data.\n\n---\n\n# Installation\n\n1. Clone the repo\n\n```bash\ngit clone https://github.com/yourusername/mlp-iris-classifier.git\ncd mlp-sonar\n```\n\n2. Create a Conda enviornment\n\nIt is included an `environment.yml` for Conda users: \n\n```bash \nconda env create -f environment.yml\nconda activate mlp-sonar\n```\n\n# Usage\n\n1. Verify the dataset\n\nThe [Sonar Dataset](https://archive.ics.uci.edu/dataset/151/connectionist+bench+sonar+mines+vs+rocks) from the UCI Machine Learning Repository is already included under data/sonar.csv.\n\n2. Adjust settings\n\nOpen `config.yaml`and tweak any values you like (seed, test_size, units, etc.)\n\n3. Run the full pipeline\n\n```bash\npython run_all.py\n```\n\nThis will: \n\n- Train de MLP without data standardization and with standardized input data\n- Save the two mlp models to `models` folder\n- Evaluate and print train/test accuracy and sample predictions\n\n# Project Structure\n\n```\nmlp-iris-classifier/\n│\n├── config.yaml          # Experiment settings\n├── environment.yml      # Conda environment spec\n│\n├── data/\n│   └── sonar.csv        # Sonar Dataset\n│\n├── models/              # (Auto-created) Trained model \u0026 params\n│\n├── src/\n│   ├── config.py        # Loads config.yaml\n│   ├── data_loader.py   # Reads \u0026 splits data\n│   ├── model_builder.py # Defines the Keras MLP\n│   ├── train.py         # Hyperparameter search \u0026 model saving\n│   └── evaluate.py      # Loads model \u0026 prints metrics\n│\n└── run_all.py           # Runs train.py then evaluate.py\n```\n\n# Dependencies \n\n- Python 3.7+\n- numpy, scikt-learn, tensorflow, scikeras, joblib, PyYAML\n\nWith Conda:\n\n```bash \nconda env create -f environment.yml\nconda activate mlp-sonar\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmarta-barea%2Fmlp-sonar-classifier","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmarta-barea%2Fmlp-sonar-classifier","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmarta-barea%2Fmlp-sonar-classifier/lists"}