A python library to build Model Trees with Linear Models at the leaves.
Predicting solar energy using machine learning (LSTM, PCA, boosting). This is our CS 229 project from autumn 2017. Report and poster are included.
The 4th Place Solution to the 2019 ACM Recsys Challenge by Team RosettaAI
Programmable Decision Tree Framework
Swift wrapper for XGBoost gradient boosting machine learning framework with Numpy and TensorFlow support.
MLJ.jl interface for JLBoost.jl
CSE601 Course Projects - Fall 2017
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.
Scripts, figures and working notes for the participation in FungiCLEF-2022, part of the 13th CLEF Conference, 2022
Built Random Forest and GBDT using XGBOOST model on Amazon fine food review dataset
Scripts, figures and working notes for the participation in SnakeCLEF-2022, part of the 13th CLEF Conference, 2022
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
LASSO and Boosting for Regression on Communities and Crime data
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
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.…
A from-scratch, educational implementation of the XGBoost algorithm for binary classification
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…
This project presents an end-to-end Machine Learning solution for predicting whether a breast tumor is Benign or Malignant using diagnostic medical data. The objective is to assist in early breast cancer detection by building accurate and interpretable classification models.
Zepto Order Analysis to Predict Unique Orders from a range of Products
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