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#

boosting-tree

Here are 31 public repositories matching this topic...

A python library to build Model Trees with Linear Models at the leaves.

  • UpdatedJul 19, 2024
  • Jupyter Notebook

Predicting solar energy using machine learning (LSTM, PCA, boosting). This is our CS 229 project from autumn 2017. Report and poster are included.

  • UpdatedJun 29, 2021
  • Python

Swift wrapper for XGBoost gradient boosting machine learning framework with Numpy and TensorFlow support.

  • UpdatedAug 29, 2020
  • Swift

MLJ.jl interface for JLBoost.jl

  • UpdatedMar 29, 2021
  • Julia

This project focuses on segmenting customers based on their tenure, creating "cohorts", allowing us to examine differences between customer cohort segments and determine the best tree based ML model.

  • UpdatedSep 28, 2021
  • Jupyter Notebook

Scripts, figures and working notes for the participation in FungiCLEF-2022, part of the 13th CLEF Conference, 2022

  • UpdatedApr 8, 2024
  • Python

Microsoft Bingのランキングの重みを自然言語的に解釈、表現します

  • UpdatedFeb 5, 2018
  • Python

Scripts, figures and working notes for the participation in SnakeCLEF-2022, part of the 13th CLEF Conference, 2022

  • UpdatedMar 3, 2023
  • Python

Building classification models to predict if a loan application is approved. Using under-sampling, bagging and boosting to tackle the problem of with unbalanced dataset

  • UpdatedJul 10, 2019
  • Jupyter Notebook

A from-scratch, educational implementation of the XGBoost algorithm for binary classification

  • UpdatedNov 27, 2025
  • Jupyter Notebook

Predicted the breast cancer in patient using Ensemble Techniques and evaluated the model

  • UpdatedApr 22, 2021
  • Jupyter Notebook

Problem Moving from traditional energy plans powered by fossils fuels to unlimited renewable energy subscriptions allows for instant access to clean energy without heavy investment in infrastructure like solar panels, for example. One clean energy source that has been gaining popularity around the world is wind turbines. Turbines are massive str…

  • UpdatedJul 20, 2021
  • Jupyter Notebook

In this project we are tryinbg to create unredactor. Unredactor will take a redacted document and the redacted flag as input, inreturn it will give the most likely candidates to fill in redacted location. In this project we are only considered about unredacting names only. The data that we are considering is imdb data set with many review files.…

  • UpdatedNov 10, 2021
  • Python

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