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Contains the *Classification* models trained on `Toy Datasets`.\n\n* **RWD_classification** - Contains the *Classification* models trained on `Real World Datasets`.\n\n* **TD_regression** - Contains the *Regression* models trained on `Toy Datasets`.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n## Classification and Regression Models\n\n* Classification\n  - K Nearest Neighbor (KNN) - K Neighbor Classifier\n  - Support Vector Machine (SVM) - Support Vector Classification (SVC)\n  - Logistic Regression (LR)\n  - Random Forest (RF) - Random Forest Classifier\n  - Multi-layer Perceptron (MLP) - Multi-layer Perceptron Classifier\n  - Stochastic Gradient Descent (SGD) - Stochastic Gradient Descent Classifier\n\n* Regression\n  - Linear Regression\n  - Ridge Regression\n  - Lasso Regression\n  - Elastic Net\n  - Decision Tree -  Decision Tree Regressor\n  - Random Forest - Random Forest Regressor\n  - Gradient Boosting - Gradient Boosting Regressor\n  - Support Vector Machine (SVM) - Support Vector Regression (SVR)\n  - K Nearest Neighbor (KNN) - K Neighbors Regressor\n  - Multi-layer Perceptron (MLP) - MLP Regressor\n\n\n## Sci-kit Library Datasets\n\nScikit-learn comes with a few small standard datasets, both for Classification and Regression.\n\n#### Toy Dataset\n\n* Classification\n  - load_iris\n  - load_digits\n  - load_wine\n  - load_breast_cancer\n\n* Regression\n  - load_diabetes\n\n\nLink: https://scikit-learn.org/stable/datasets/toy_dataset.html\n\n\n#### Real World Dataset\n\nfetch_olivetti_faces - Classification\n\nLink: https://scikit-learn.org/stable/datasets/real_world.html\n\n\n\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhaseeeb21%2Fmachine-learning-models","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhaseeeb21%2Fmachine-learning-models","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhaseeeb21%2Fmachine-learning-models/lists"}