supuna97/divorce-prediction

The aim of this machine learning application is that it can use to predict divorce. The dataset is the Divorce Prediction dataset by Larxel from the website: Kaggle. There are few models tested when developing the application, including Tree-based models like Decision trees, Random forest, XGBoost and a binary classification model called Logisti...

The aim of this machine learning application is that it can use to predict divorce. The dataset is the Divorce Prediction dataset by Larxel from the website: Kaggle. There are few models tested when developing the application, including Tree-based models like Decision trees, Random forest, XGBoost and a binary classification model called Logistic Regression. In addition, there are some data pre-processing techniques also used to analyze and normalize the dataset. Then, after applying the normalized datasets to all the models and predicting, some model optimizing methods used to get more accuracy. To build the final application, I have used the Flask framework in Python to expose the model via a REST web API. And i have used Reactjs framework to view frontend. To run as an artefact, I have used the requirements.txt technique in Pip dependency management.