Closed void-02 closed 2 years ago
Added different classification models to predict diabetes. Here are the classification accuracies:- KNN (n neighbors = 3) = 71.4% KNN (n neighbors = 5) = 71.4% KNN (n neighbors = 7) = 68.8% KNN (n neighbors = 10) = 70.1% KNN (Best Parameters) = 74.02% MLP (hidden layer size = 50) = 71.4% MLP (hidden layer size = 100) = 66.2% MLP (hidden layer size = 150) = 70.1% MLP (hidden layer size = 200) = 70.1% MLP (Best Parameters) = 71.4% LGBM Classifier = 74.02% LGBM Classifier = 75.32% SVM = 75.32% Logistic Regression = 75.32% Random Forest = 81.81%
Let me know if any changes are required
Hey, @void-02 Do add a readme file of explaining about your project
LGTM! @void-02 🚀 Thanks for your valuable contribution ✨ Hope you like the repo Do Give a star to this repo ✨
Added different classification models to predict diabetes. Here are the classification accuracies:- KNN (n neighbors = 3) = 71.4% KNN (n neighbors = 5) = 71.4% KNN (n neighbors = 7) = 68.8% KNN (n neighbors = 10) = 70.1% KNN (Best Parameters) = 74.02% MLP (hidden layer size = 50) = 71.4% MLP (hidden layer size = 100) = 66.2% MLP (hidden layer size = 150) = 70.1% MLP (hidden layer size = 200) = 70.1% MLP (Best Parameters) = 71.4% LGBM Classifier = 74.02% LGBM Classifier = 75.32% SVM = 75.32% Logistic Regression = 75.32% Random Forest = 81.81%
Let me know if any changes are required