{"id":20299161,"url":"https://github.com/aysenurcftc/credit_score-classification","last_synced_at":"2026-05-15T13:03:54.246Z","repository":{"id":245286991,"uuid":"804479465","full_name":"aysenurcftc/Credit_Score-Classification","owner":"aysenurcftc","description":null,"archived":false,"fork":false,"pushed_at":"2024-07-06T09:29:40.000Z","size":19,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-10-05T16:51:28.171Z","etag":null,"topics":["classification","credit-scoring","csv","finance","logistic-regression","neural-network","nn","scikit-learn"],"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/aysenurcftc.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-05-22T17:03:44.000Z","updated_at":"2024-07-06T12:08:28.000Z","dependencies_parsed_at":"2024-06-21T05:49:10.565Z","dependency_job_id":"8c7b9bd5-5c22-4c40-892f-cdc943cd7073","html_url":"https://github.com/aysenurcftc/Credit_Score-Classification","commit_stats":null,"previous_names":["aysenurcftc/credit_score-classification"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/aysenurcftc/Credit_Score-Classification","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aysenurcftc%2FCredit_Score-Classification","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aysenurcftc%2FCredit_Score-Classification/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aysenurcftc%2FCredit_Score-Classification/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aysenurcftc%2FCredit_Score-Classification/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/aysenurcftc","download_url":"https://codeload.github.com/aysenurcftc/Credit_Score-Classification/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aysenurcftc%2FCredit_Score-Classification/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33067476,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-15T11:35:32.926Z","status":"ssl_error","status_checked_at":"2026-05-15T11:35:31.362Z","response_time":103,"last_error":"SSL_connect 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datasets.\n\n\n## Installation\n\n\n\n```bash\npip install -r requirements.txt\n```\n    \n## Usage/Examples\n\n```\nusage: main.py [-h] [--run_mode RUN_MODE] [--dataset DATASET] [--model_type MODEL_TYPE] [--imputing_type_numerical IMPUTING_TYPE_NUMERICAL]\n               [--imputing_type_categorical IMPUTING_TYPE_CATEGORICAL] [--split_ratio SPLIT_RATIO] [--filepath FILEPATH]\n\nTrain a model on a specified dataset.\n\noptions:\n  -h, --help            show this help message and exit\n  --run_mode RUN_MODE   Mode to run the script in, e.g., training or testing\n  --dataset DATASET     Dataset to use for training\n  --model_type MODEL_TYPE\n                        Type of model to use, e.g., 'logistic regression' or 'NN'\n  --imputing_type_numerical IMPUTING_TYPE_NUMERICAL\n                        Imputing strategy for numerical features\n  --imputing_type_categorical IMPUTING_TYPE_CATEGORICAL\n                        Imputing strategy for categorical features\n  --split_ratio SPLIT_RATIO\n                        Train-test split ratio\n  --filepath FILEPATH   Path to the dataset file\nNone\nusage: main.py [-h] [--run_mode RUN_MODE] [--dataset DATASET] [--model_type MODEL_TYPE] [--imputing_type_numerical IMPUTING_TYPE_NUMERICAL]\n               [--imputing_type_categorical IMPUTING_TYPE_CATEGORICAL] [--split_ratio SPLIT_RATIO] [--filepath FILEPATH]\n\nTrain a model on a specified dataset.\n\noptions:\n  -h, --help            show this help message and exit\n  --run_mode RUN_MODE   Mode to run the script in, e.g., training or testing\n  --dataset DATASET     Dataset to use for training\n  --model_type MODEL_TYPE\n                        Type of model to use, e.g., 'logistic regression' or 'NN'\n  --imputing_type_numerical IMPUTING_TYPE_NUMERICAL\n                        Imputing strategy for numerical features\n  --imputing_type_categorical IMPUTING_TYPE_CATEGORICAL\n                        Imputing strategy for categorical features\n  --split_ratio SPLIT_RATIO\n                        Train-test split ratio\n  --filepath FILEPATH   Path to the dataset file\n\n\n```\n\n\n## Deployment\n\nTo deploy this project run\n\n```bash\n   docker build -t ml_proje . \n   docker run ml_proje  --run_mode training --dataset statlog_german_credit_data  --model_type NN  --imputing_type_numerical median --imputing_type_categorical mode --split_ratio 0.7 --filepath data/statlog_german_credit_data.csv\n\n```\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faysenurcftc%2Fcredit_score-classification","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Faysenurcftc%2Fcredit_score-classification","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faysenurcftc%2Fcredit_score-classification/lists"}