boosting
There are 366 repositories under boosting topic.
SMARTboost.jl
SMARTboost (boosting of smooth symmetric regression trees)
logitboost
LogitBoost classification algorithm built on top of scikit-learn
Boosting-multitask-learning-on-graphs
A boosting procedure for multitask learning on graph-structured data
steam-hour-booster
Farm your in-game hours on Steam
ecgn
Concepts used: kNN, SVM, boosting (XGBoost, Gradient boosting, Light GBM, AdaBoost, Random Forests), deep learning (CNN, LSTM), ensembles (model stacking), transfer learning.
song-popularity-prediction
Song Popularity Prediction Using Machine Learning Algorithms
BooVAE
Code repository of the paper "BooVAE: Boosting Approach for Continual Learning of VAE" published at NeurIPS 2021. https://arxiv.org/abs/1908.11853
Dada
source code of AISTATS 2020 paper: Fully Decentralized Joint Learning of Personalized Models and Collaboration Graphs
EvoLinear.jl
Linear models
Spam-Messages-Detection
Project building ML & DL models to detect spam messages.
simple-gradient-boosting
Very simple and short implementation of gradient boosting in 18 lines of code
Machine-Learning-Handwritte-Notes
Entire Machine Learning Hand Written Notes
Machine-Learning
Regression, Classification, Clustering, Dimension-reduction, Anomaly detection
Machine-Learning-Codes
Machine Learning is not a MAGIC but MATH
Avito-Demand-Prediction-Challenge
It is a Competition for Regression Challenge held by Kaggle, It is based on a Avito Dataset whose size is 123GB which can be accessed from Kaggle, I have done Data Pre-processing, feature engineering, feature extraction, data visualization, machine learning, stacking and boosting
Titanic-Passenger-Survival-Prediction
Using Classification Techniques, Data reprocessing, Feature Engineering, Feature Extraction and Classification Algorithms from Machine Learning to Predict who can Survive the attack of Tsunami.
Kaggle-House-Prices-Advanced-Regression-Techniques
House Prices: Advanced Regression Techniques - Kaggle competition
mlflow-demo
Simple Demo of MLflow Project
XLabel
XLabel: An Explainable Data Labeling Assistant
ATPTennisMatchPredictions
Tennis Match Predictions using Machine Learning
stackboost
Open source gradient boosting library
Predicting_Money_Spent_at_Resort
It is From Analytics Vidhya Hackathons, Sponsored by Club Mahindra. It is based on Regression Problem, Where Accuracy matters the most, It is measured by RMSE Score. Different Techniques such as Stacking, Ensembling, Boosting and Scientific Operations such box-cox Operations to reduce skewness of the data.
AdaBoost
A simplified implement of Adaptive boosting.
GreedyBoost
Implementation of Modified Online Adaboost-ing algorithm
Discord-Boost-Bot
a discord bot which boost ur server on command
Machine-Failure_Prediction_EnsembleMethods_ModelTuning
This project predicts wind turbine failure using numerous sensor data by applying classification based ML models that improves prediction by tuning model hyperparameters and addressing class imbalance through over and under sampling data. Final model is productionized using a data pipeline
Analysis-and-prediction-of-online-shoppers-purchasing-intention-using-various-algorithms-CAPSTONE
Build a predictive machine learning model that could categorize users as either, revenue generating, and non-revenue generating based on their behavior while navigating a website. In order to predict the purchasing intention of the visitor, aggregated page view data kept track during the visit along with some session is used and user information as input to machine learning algorithms. Oversampling/Undersampling and feature selection techniques are applied to improve the success rates and scalability of the models.
Machine_Learning_Hackathons
Machine learning and Deep Learning Hackathon Solutions
Credit-Risk-Analysis
Predicting the ability of a borrower to pay back the loan through Traditional Machine Learning Models and comparing to Ensembling Methods
house_prices_melbourne
A compilation of different models that predict a home's value (in Melbourne, Australia) and determine which model performs better and why.
Societe-General
Solution for ENS - Societe Generale Challenge (1st place).
snapboost
Heterogeneous Newton Boosting Machine using decision trees and kernel ridges as learners.
Tutorial-Machine-Learning-Arboles
Los árboles de decisión son uno de los algoritmos clásicos de machine learning ya que nos ayudan a visualizar las predicciones hechas por nuestro modelo. En este tutorial vemos su uso para regresiones lineares y clasificación, así como herramientas de ensamble como bagging y boosting.
Cascade_Toolbox
A toolbox to simplify training, testing, and running HAAR/LBP cascades for object detection
ml-earthquake
machine learning semester project to predict earthquake damage levels
weightedFastText
Weighted FastText is a library for fast text classification with weighted examples