Skip to content

Latest commit

 

History

History
28 lines (16 loc) · 884 Bytes

File metadata and controls

28 lines (16 loc) · 884 Bytes

Disease-Prediction-based-on-Symptoms

Disease Prediction based on Symptoms using Machine Learning Algorithms with User Interface Machine Learning Bootcamp - A Project based approach

Machine Learning Project from Scrath Project Title: Disease Prediction based on symptoms using machine learning Steps: 1.Setup Environment (install Pycharm,pandas,matplotlib,seaborn,Scikit-learn, tkinter) 2.Download Dataset and understand dataset (kaggle) 3.Data preprocessing (removing missing values,encoding) 4.Split the data into training set and testing set(train_test_split function) 5.Choose machine learning algorithm (SVM, GaussianNB, Random Forest) 6.Buid the model (fit function) 7.Predict the results (predict function) 8.Performance analysis (Accuracy score, confusion matrix) 9.Design User Interface (tkinter, Label, Button, Text, Radio Button) 10.Integrate UI and Algorithm