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

The 4th Place Solution to the 2019 ACM Recsys Challenge by Team RosettaAI

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

Programmable Decision Tree Framework

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

Machine Learning Algorithms in Fortran

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

LASSO and Boosting for Regression on Communities and Crime data

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

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

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

classfication of cloud image pixels

gene classification based on partial-order rule mining

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…

Datascience hands on code

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