Devdiscourse

Banks could strengthen credit card fraud screening with ensemble machine learning model

Read more about Banks could strengthen credit card fraud screening with ensemble machine learning model on Devdiscourse ...
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, ...
IEEE

An Innovative Analysis to Improve the Performance by Blocking the Pop-ups of Web Applications with XGBoost Algorithm over K-Means Algorithm

Abstract: The focus of the research is to utilise the XGBoost algorithm in comparison to the K-Means algorithm is to prevent pop-up windows from showing up on a web application. The K-Means Algorithm ...

Satellite data and multispectral imagery advance glacier lake depth measurement

As global warming accelerates, the increasing number of supraglacial lakes and the need to accurately measure their depths have become critical for understanding ice sheet mass balance and sea-level ...
Frontiers

Application of machine learning algorithms for prediction of ultraviolet absorption spectra of chromophoric dissolved organic matter (CDOM) in seawater

* - diluted samples, # - samples spiked with standard solution. The BPNN model is trained by continuously adjusting the weights and thresholds of each neuron, and the training processes consist ...
Scientific Research Publishing

Supply Chain Demand Forecast Based on SSA-XGBoost Model ()

Supply chain management usually faces problems such as high empty rate of transportation, unreasonable inventory management, and large material consumption caused by inaccurate market demand forecasts ...