专题:Data Mining Algorithms and Applications

This cluster of papers covers a wide range of topics in data mining, including frequent pattern mining, association rule mining, sequential pattern mining, machine learning, decision trees, interestingness measures, high utility itemsets, temporal data mining, and knowledge discovery.
最新文献
Automated research methodology classification using machine learning

article Full Text OpenAlex

Oferta On-Line do “Curso Introdutório de R Statistical”: um Relato de Experiência

article Full Text OpenAlex

A technological, data‐oriented design journey for teaching and learning business intelligence and analytics projects

article Full Text OpenAlex

Klasifikasi Penyakit Paru-Paru Menggunakan Data Mining Decision Tree

article Full Text OpenAlex

Customer Churn Prediction Model Using Gravitational Search Algorithm

book-chapter Full Text OpenAlex

Segmentation of Business Interest using FIMIX-PLS and REBUS-PLS

book-chapter Full Text OpenAlex

The International Workshop on Spatio-Temporal Data Mining from the Web

article Full Text OpenAlex

EFF BI: Effortless Business Intelligence -Text-to-Vis from LLM Agents

article Full Text OpenAlex

A Comparative Analysis of DBSCAN, K-Means and Agglomerative Clustering Algorithms for Geospatial Data

book-chapter Full Text OpenAlex

Decision Tree Models

book-chapter Full Text OpenAlex

近5年高被引文献
An Introduction to Statistical Learning: with Applications in R

book Full Text OpenAlex 2997 FWCI78.492

E-Commerce Promotional Products Selection Using SWARA and TOPSIS

article Full Text OpenAlex 1548 FWCI1582.746

Data Mining Concepts and Techniques Third Edition

article Full Text OpenAlex 1223 FWCI81.496

Visualizations with statistical details: The 'ggstatsplot' approach

article Full Text OpenAlex 1045 FWCI88.499

An Introduction to Statistical Learning

book Full Text OpenAlex 1018 FWCI193.579

K-means clustering algorithms: A comprehensive review, variants analysis, and advances in the era of big data

article Full Text OpenAlex 948 FWCI124.903

The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation

article Full Text OpenAlex 630 FWCI64.274

Proceedings of the 55th Annual ACM Symposium on Theory of Computing

paratext Full Text OpenAlex 616 FWCI0

Spatial Data Science

book Full Text OpenAlex 441 FWCI211.199

Data mining in clinical big data: the frequently used databases, steps, and methodological models

review Full Text OpenAlex 400 FWCI23.509