Brownstein, Holland & Knight, K&L Gates, Squire Patton Boggs and Hogan Lovells all reported increases in their lobbying revenue compared with Q1 of this year. Kirkland & Ellis and Simpson Thacher & ...

Abstract: In this paper, an improved K-means clustering algorithm, EGLK-Means, is proposed, which optimizes the clustering results by enhancing global and local information. The traditional K-means ...

This project demonstrates how to apply K-Means Clustering to analyze and group houses based on various features, using the House Price Prediction Dataset. The objective is to segment the data into ...

ABSTRACT: Domaining is a crucial process in geostatistics, particularly when significant spatial variations are observed within a site, as these variations can significantly affect the outcomes of ...

1 Facultad de Ingeniería, Universidad Andres Bello, Santiago, Chile. 2 Department of Mining Engineering, Universidad de Chile, Santiago, Chile. 3 Advanced Mining Technology Center, Universidad de ...

'K-Means clustering is an unsupervised learning algorithm that is used to group data into K clusters based on feature similarity. Each data point belongs to the cluster whose centroid is the nearest. ...

1 Northwest Branch of Research Institute of Petroleum Exploration and Development, PetroChina, Lanzhou, China 2 Xinjiang Oilfield Company, PetroChina, Karamay, China Automatic picking of seismic ...