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#

xgboost-algorithm

Here are 431 public repositories matching this topic...

awesome-gradient-boosting-papers

Extension of the awesome XGBoost to linear models at the leaves

  • UpdatedJun 24, 2019
  • Python

A lightweight gradient boosted decision tree package.

  • UpdatedApr 25, 2025
  • Rust

Tuning XGBoost hyper-parameters with Simulated Annealing

  • UpdatedApr 26, 2017
  • Jupyter Notebook

XGBoost, LightGBM, LSTM, Linear Regression, Exploratory Data Analysis

  • UpdatedJan 9, 2020
  • Jupyter Notebook
fantasy-sports-prediction

We have used our skill of machine learning along with our passion for cricket to predict the performance of players in the upcoming matches using ML Algorithms like random-forest and XG Boost

  • UpdatedMar 28, 2024
  • Python

Perform a survival analysis based on the time-to-event (death event) for the subjects. Compare machine learning models to assess the likelihood of a death by heart failure condition. This can be used to help hospitals in assessing the severity of patients with cardiovascular diseases and heart failure condition.

  • UpdatedNov 4, 2023
  • Jupyter Notebook

Designed web app employs the Streamlit Python library for frontend design and communicates with backend ML models to predict the probability of diseases. It's capable of predicting whether someone has Diabetes, Heart issues, Parkinson's, Liver conditions, Hepatitis, Jaundice, and more based on the provided symptoms, medical history, and results.

  • UpdatedJan 6, 2025
  • Python

Career Guidance System Using Machine Learning Techniques

  • UpdatedNov 30, 2020
  • Jupyter Notebook

Modified XGBoost implementation from scratch with Numpy using Adam and RSMProp optimizers.

  • UpdatedJul 24, 2020
  • Jupyter Notebook

Binary Classification for detecting intrusion network attacks. In order, to emphasize how a network packet with certain features may have the potentials to become a serious threat to the network.

  • UpdatedDec 19, 2021
  • Jupyter Notebook

A binary classification model is developed to predict the probability of paying back a loan by an applicant. Customer previous loan journey was used to extract useful features using different strategies such as manual and automated feature engineering, and deep learning (CNN, RNN). Various machine learning algorithms such as Boosted algorithms (…

  • UpdatedSep 13, 2022
  • Jupyter Notebook

Machine Learning Project using Kaggle dataset

  • UpdatedFeb 17, 2019
  • Jupyter Notebook

The python notebook is on googles new collabatory tool. Its a churn model being run on 3 different algorithms to compare.

  • UpdatedMar 3, 2018
  • Jupyter Notebook

This repository contains code and data for analyzing real estate trends, predicting house prices, estimating time on the market, and building an interactive dashboard for visualization. It is structured to cater to data scientists, real estate analysts, and developers looking to understand property market dynamics.

  • UpdatedJan 16, 2025
  • Jupyter Notebook

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