| | --- |
| | metadata: |
| | language: en |
| | library_name: scikit-learn |
| | tags: |
| | - classification |
| | - machine-learning |
| | - tabular-data |
| | - sklearn |
| | - healthcare |
| | - clinical-decision-support |
| | license: mit |
| | datasets: |
| | - Benchmark datasets |
| | model-type: multi-model-repository |
| | author: Thyagharajan K K |
| | pipeline_tag: tabular-classification |
| | inference: true |
| | flags: |
| | - cpu |
| | - allow_fork |
| | - allow_metrics |
| | emoji: 📊 |
| | colorFrom: blue |
| | colorTo: indigo |
| | --- |
| | |
| | # 🧠 KKT-ML-Models |
| |
|
| | This repository serves as a centralized suite of **machine learning models** developed and trained |
| | by Dr.K.K. Thyagharajan for research, experimentation, and deployment across multiple domains. |
| | The repository is organized **by application domain**, with each domain containing one or more |
| | trained models, preprocessing pipelines, and documentation. |
| |
|
| | The repository supports: |
| | - Reproducible research |
| | - Model reuse and deployment |
| | - Separation of preprocessing and inference artifacts |
| | - Compatibility with Hugging Face Spaces and APIs |
| |
|
| | ## 🔍 Domains Covered |
| | - Diabetes prediction (tabular clinical data) |
| | - Additional healthcare and ML domains will be added incrementally |
| | --- |
| |
|
| | ## 📂 Repository Structure |
| | ```text |
| | KKT-ML-Models/ |
| | │ |
| | ├── README.md |
| | │ |
| | └── diabetic_models/ |
| | │ |
| | ├── README.md |
| | │ |
| | ├── logistic_reg_diabetic.pkl |
| | │ (Baseline batch Logistic Regression model) |
| | │ |
| | └── SGD_scaler_diabetic_models/ |
| | │ |
| | ├── README.md |
| | │ |
| | ├── SGD_model.pkl |
| | │ (Final SGD-based logistic regression classifier) |
| | │ |
| | └── SGD_scaler.pkl |
| | (Fitted StandardScaler used during training) |
| | ``` |
| | --- |
| |
|
| | ## 📦 Model Collections |
| | Each subdirectory corresponds to a **domain-specific model collection**. |
| | ``` |
| | Models are released with: |
| | - Serialized artifacts |
| | - Explicit preprocessing components |
| | - Clear inference documentation |
| | - Licensing and citation metadata |
| | ``` |
| |
|
| | --- |
| | ## 🧰 Technology Stack |
| |
|
| | - Python ≥ 3.8 |
| | - scikit-learn |
| | - numpy |
| | - pandas |
| | - joblib |
| |
|
| | --- |
| | ## 📜 License |
| | This repository is released under the MIT License. |
| | See the `LICENSE` file for full terms. |
| |
|
| | --- |
| | ## 📖 Citation |
| | If you use these models in academic work, please cite using the `CITATION.cff` file. |
| |
|
| | --- |
| | ## 👨💻 Maintainer |
| |
|
| | **Dr. Thyagharajan K K** |
| | Professor & Dean (Research) |
| | RMD Engineering College |
| | 📧 kkthyagharajan@yahoo.com |
