Popular GitHub Repositories for Voting Regressor

Deep Hough Voting for 3D Object Detection in Point Clouds

A unified ensemble framework for PyTorch to improve the performance and robustness of your deep learning model.

Code for ICCV2021 paper PARE: Part Attention Regressor for 3D Human Body Estimation

Learning to create Machine Learning Algorithms

[ECCV-20] Official PyTorch implementation of HoughNet, a voting-based object detector.

Agentic Framework for Java, written in 100% Java using Gemini, OpenAI, LocalAI, Anthropic. Build Autonomous Agents in Java with Multi AI voting mechanism. Convert Prompt to HTTP REST Calls, Java Method calls, Shell script calls or swagger rest api calls. Selenium AI Integration, Image processing with AI, Actions on Images with AI

? Conformal Tights adds conformal prediction of coherent quantiles and intervals to any scikit-learn regressor or Darts forecaster

Building Time series forecasting models, including the XGboost Regressor, GRU (Gated Recurrent Unit), LSTM (Long Short-Term Memory), CNN (Convolutional Neural Network), CNN-LSTM, and LSTM-Attention. Additionally, hybrid models like GRU-XGBoost and LSTM-Attention-XGBoost for Electricity Demand and price prediction

A Machine Learning Project implemented from scratch which involves web scraping, data engineering, exploratory data analysis and machine learning to predict housing prices in New York Tri-State Area.

This project provides implementations with Keras/Tensorflow of some deep learning algorithms for Multivariate Time Series Forecasting: Transformers, Recurrent neural networks (LSTM and GRU), Convolutional neural networks, Multi-layer perceptron

Modeling time series of electricity spot prices using Deep Learning.

To design a predictive model using xgboost and voting ensembling techniques and extract insights from the data using pandas, seaborn and matplotlib

An advanced machine learning model utilizes a Random Forest Regressor to generate betting recommendations for Major League Baseball (MLB) games.

Classifying Audio to Emotion

The project aimed to implement Deep NN / RNN based solution in order to develop flexible methods that are able to adaptively fillin, backfill, and predict time-series using a large number of heterogeneous training datasets.

Contains code for a voting classifier that is part of an ensemble learning model for tweet classification (which includes an LSTM, a bayesian model and a proximity model) and a system for weighted voting

The Multimodal Sarcasm Detection System detects sarcasm in multimedia content using image-caption generation and NLP. It achieved 1st place in UITC2024 by classifying sarcasm into four categories: image, text, multi sarcasm, and not sarcasm.

Supervised Machine Learning Analysis Using Classification Models

An example of how the LIME algorithm can be used to provide real-world insight into the decision processes of a 'black-box' machine learning algorithm - in this case a Radom Forest regressor.

Crypto & Stock* price prediction with regression models.