The Banker

Banks and regulators clash over ‘black box’ AI credit risk

Earlier this year when a UK Treasury Committee released a report warning that regulators’ complacency on AI in financial ...
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, ...
Nature

Harnessing LSTM and XGBoost algorithms for storm prediction

Storms can cause significant damage, severe social disturbance and loss of human life, but predicting them is challenging due to their infrequent occurrence. To overcome this problem, a novel deep ...
LinkedIn

Next Best Action using Machine Learning (XGBoost)

Today I am going to talk about a very important business problem ' Next Best Action' (NBA) and how machine learning is helping to model the NBA. I will start by giving an example of what the NBA is ...
Nature

Comparative performances of machine learning algorithms in radiomics and impacting factors

Radiomics can be defined as the quantitative extraction of a high number of features from medical images for discovery of new predictive, diagnostic or prognostic imaging biomarkers of disease.
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 ...