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Go module to build a decisional tree from a Json file and run a search through it

Advanced_Data_Integration_Project

The implementation for paper Machine Unlearning in Gradient Boosting Decision Trees (Accepted on KDD 2023), supporting training and unlearning.

This novel model and associated paper proposes the use of a two-stage K- means clustering for variable selection and then using decision trees and support vector regressors for day-ahead load forecasting in the CAISO electricity market.

A full stack python Flask artificial intelligence project capable of beating the human user in Rock Paper Scissors over 60% of the time using a custom scoring system to ensemble six models (naïve logic-based, decision tree, neural network) trained on both game-level and stored historical data in ... Read more

Machine learning project using the Kaggle Heart Disease Health Indicators dataset to predict heart disease risk. Covers preprocessing, EDA, and training models (Logistic Regression, Random Forest, XGBoost, SVM, KNN, Decision Tree, Naive Bayes) with evaluation via Accuracy, ROC-AUC, and Confusion ... Read more

This project explores UK road accident data with the goal of predicting accident severity using machine learning. Techniques include clustering (KMeans, DBSCAN), association rule mining (Apriori), and classification models (Random Forest, Decision Tree, Gradient Boosting) enhanced by SMOTE for cl... Read more

This repository represent an AI method to classify an article as clickbait or non-clickbait

Machine Learning (ML) develops computer programs that automatically improve their performance through experience. This includes learning many types of tasks based on many types of experience, e.g. spotting high-risk medical patients, recognizing speech, classifying text documents, detecting credi... Read more

Analysis of Air Pollution prediction and time-series forecast of PM2.5 Pollutant using Machine Learning Algorithms (SVM, Decision Tree and Random Forest) and Deep Learning Algorithms (CNN, Bi-LSTM). Also considered for improved performances is random search hyper-parameter tuning using Ray-Tune w... Read more