[ICDE'20] ⚖️ A general, efficient ensemble framework for imbalanced classification. | 泛用,高效,鲁棒的类别不平衡学习框架
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Feb 5, 2024 - Python
[ICDE'20] ⚖️ A general, efficient ensemble framework for imbalanced classification. | 泛用,高效,鲁棒的类别不平衡学习框架
tools for scalable and non-intrusive parameter estimation, uncertainty analysis and sensitivity analysis
Handwritten digit recognition with MNIST & Keras
AI-CryptoTrader is a state-of-the-art cryptocurrency trading bot that uses ensemble methods to make trading decisions based on multiple sophisticated algorithms. Built with the latest machine learning and data science techniques, AI-CryptoTrader provides a powerful toolset and advanced trading stratgies for maximizing your cryptocurrency profits.
Winning 2nd place🥈at NUS CS5228 in-class Kaggle competition 2018!
This project focuses on using the AWS open-source AutoML library, AutoGluon, to predict bike sharing demand using the Kaggle Bike Sharing demand dataset.
Time series forecasting with Fourier-adjusted time dummies
Capstone project #2 for the Harvard University Professional Certificate in Data Science
Official Implementation of Track2Vec: Fairness Music Recommendation with a GPU-Free Customizable-Driven Framework EvalRS-CIKM-2022
This repository contains code archives for models that predict the risk of death from heart failure.
Predict sale prices via regression models, using PCA, k-means clustering, ensemble models, pipelines, etc.
This project studies different possibilities to make good predictions based on machine learning algorithms, but without requiring great theoretical knowledge from the users. Moreover, a software package that implements the prediction process has been developed. The software is an ensemble method that first predicts a value taking into account di…
Comparison of ensemble learning methods on diabetes disease classification with various datasets
Build a classification model to predict clients who are likely to default on their loans. Give recommendations to the bank on important features to consider while approving a loan. Concepts Used: Logistic Regression, Decision Trees, Random Forests, and Ensemble Methods
User documentation website for the Sulis tier 2 HPC service. Built using Jekyll.
This is an assignment from my Machine Learning for Mechanical Engineers course that demonstrates an understanding in decision trees and ensemble methods using scikit-learn.
This repository hosts the Cervical Cancer Image Classification project, a comprehensive effort aimed at improving the classification accuracy of Squamous Cell Carcinoma (SCC) through advanced deep learning models and ensemble techniques. The project utilizes the Herlev dataset.
Projects completed as a part of IIIT-Delhi's Post Graduation Diploma in Computer Science and Artificial Intelligence.
Predicts the qualified employee for promotion using Classification
My solutions to the data analysis and forecasting case study held by Bella & Bona
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