{"id":20619361,"url":"https://github.com/mohammed-majid/logistic-binary-email-classification","last_synced_at":"2026-05-02T05:03:22.497Z","repository":{"id":241853498,"uuid":"808012841","full_name":"Mohammed-Majid/Logistic-Binary-Email-Classification","owner":"Mohammed-Majid","description":"Binary Classification of spam/ham emails","archived":false,"fork":false,"pushed_at":"2024-05-30T08:12:52.000Z","size":22,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-17T05:08:30.481Z","etag":null,"topics":["binary-classification","logistic-regression","scikit-learn"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/Mohammed-Majid.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":"2024-05-30T07:59:38.000Z","updated_at":"2024-08-06T14:43:44.000Z","dependencies_parsed_at":null,"dependency_job_id":"8ca4647a-22a6-4007-bd8d-d41602d4f556","html_url":"https://github.com/Mohammed-Majid/Logistic-Binary-Email-Classification","commit_stats":null,"previous_names":["mohammed-majid/logistic-binary-email-classification"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Mohammed-Majid%2FLogistic-Binary-Email-Classification","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Mohammed-Majid%2FLogistic-Binary-Email-Classification/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Mohammed-Majid%2FLogistic-Binary-Email-Classification/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Mohammed-Majid%2FLogistic-Binary-Email-Classification/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Mohammed-Majid","download_url":"https://codeload.github.com/Mohammed-Majid/Logistic-Binary-Email-Classification/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":242277652,"owners_count":20101536,"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":["binary-classification","logistic-regression","scikit-learn"],"created_at":"2024-11-16T12:11:28.386Z","updated_at":"2026-05-02T05:03:22.434Z","avatar_url":"https://github.com/Mohammed-Majid.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Email Binary Classification using Logistic Regression\nThis repository contains code for a binary classification task: predicting whether an email is spam (1) or ham (0) using logistic regression.\n\n## Overview\nThe main script email_classification.py demonstrates the process of:\n\n- Pre-processing: Loading the dataset, checking for missing values, and splitting it into training and testing sets.\n- Feature Extraction: Utilizing TF-IDF Vectorization to convert text data into numerical features.\n- Modeling: Training a logistic regression model on the extracted features.\n- Evaluation: Assessing the model's performance on both training and testing data, including accuracy, confusion matrix, and classification report.\n- Prediction: Accepting user input (email text) and predicting whether it's spam or ham.\n\n## Usage\n- Clone the Repository\n\n- Install Dependencies: Make sure you have the necessary dependencies installed. You can install them using pip:\n```\npip install numpy pandas scikit-learn seaborn\n```\n- Run the Script\n\n- Input Email: When prompted, enter an email text to classify it as spam or ham.\n\n## Dataset\nThe dataset email_classification.csv contains email texts labeled as spam or ham.\n\n## Requirements\n- Python 3.x\n- numpy\n- pandas\n- scikit-learn\n- seaborn\n  \n## Project Structure\n- Model.ipynb: The file that contains the script.\n- email_classification.csv: The dataset used to train and test the model.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmohammed-majid%2Flogistic-binary-email-classification","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmohammed-majid%2Flogistic-binary-email-classification","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmohammed-majid%2Flogistic-binary-email-classification/lists"}