VentureBeat

Beyond the lakehouse: Fundamental's NEXUS bypasses manual ETL with a native foundation model for tabular data

The deep learning revolution has a curious blind spot: the spreadsheet. While Large Language Models (LLMs) have mastered the nuances of human prose and image generators have conquered the digital ...
GitHub

Explain XGBoost models with the Hoeffding functional decomposition.

treehfd is a Python module to compute the Hoeffding functional decomposition of XGBoost models (Chen and Guestrin, 2016) with dependent input variables, using the TreeHFD algorithm. This decomposition ...
IEEE

An XGBoost-SHAP Model for Energy Demand Prediction With Boruta–Lasso Feature Selection

Abstract: Energy demand prediction is essential in ensuring national energy security, promoting high-quality economic development, advancing sustainable development, optimizing the energy structure, ...
InfoWorld

14 popular AI algorithms and their uses

Large language models have captured the news cycle, but there are many other kinds of machine learning and deep learning with many different use cases. Amid all the hype and hysteria about ChatGPT, ...
Scientific Research Publishing

Research on Telecom Customer Churn Prediction Based on GA-XGBoost and SHAP ()

To address the prominent problems faced by customer churn in telecom enterprise management, a telecom customer churn prediction model integrating GA-XGBoost and SHAP is proposed. By using the ADASYN ...
Scientific Research Publishing

Machine Learning Approaches to Predict Loan Default ()

Loan lending plays an important role in our everyday life and powerfully promotes the growth of consumption and the economy. Loan default has been unavoidable, which carries a great risk and may even ...