Extract important feature sequences from xgboost models
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Updated
Oct 30, 2017 - JavaScript
Extract important feature sequences from xgboost models
An intelligent Django web-application for predicting Dublin Bus travel times. This project involves backend and frontend development, machine learning, database management, research and agile development techniques.
Determines the worthiness of the car
Fit XGBoost models online
Investigating the evolution of XGBoost in the Decision-Making Process of Android Malware Classification
Real time journey planner for Dublin Bus (Ireland). Uses ML techniques to predict journey times, implemented with Django framework.
Pima Indian Diabetes via Kaggle. Fit classification models (logistic regression, knn, random forest, xgboost) to data.
Django Web App that uses XGBoost Classifier to predict whether or not an employee needs mental health treatment.
Would you have survived the titanic? Let the data decide!
Catch Phisher is a comprehensive phishing detection kit enhanced with intelligent surveillance capabilities. The solution includes a web app, a browser extension, and the Phish Guard assistant, providing multi-layered protection against phishing. The browser extension acts as a real-time monitor, scanning URLs and cross-checking them with a db.
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