⌘+K

Pulse Explore Communities Researchers Journals

Home Communities Explore

April 30, 2014Intelligent Data Analysis

Detecting concept drift: An information entropy based method using an adaptive sliding window

Lei Du Qinbao Song Xiaolin Jia

View at Publisher

Ask AI

Bookmark

Share

Abstract

Concept drift in data stream poses many challenges and difficulties in mining this tradition-distinct database. In this paper, we focus on detecting concept drift in evolving data stream. We propose a novel method to detect concept drift using entrop

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

Du et al. (2014) studied this question.

synapsesocial.com/papers/6a1c3d4b6f692abb725f2e24 https://doi.org/10.3233/ida-140645

View at Publisher

Ask AI

Bookmark

Share

Keep reading

Synapse has enriched 5 related papers. Consider them for comparative context:

1An AI-interpretable multidimensional intelligence-driven framework for student performance prediction using local LLM-based narrative reasoningIntelligent Data Analysis · Fri,
2Explainable deep learning for Mango leaf disease recognition using AlexNet and grad-CAMIntelligent Data Analysis · Thu,
3Few-shot email spam detection for low-resource languages: A setFit-based approach on Turkish and English datasetsIntelligent Data Analysis · Wed,
4Flexible fuzzy reinforcement learning MCDM approach for bioprinter selection through resolving criteria dependenciesIntelligent Data Analysis · Mon,
5Evaluating ChatGPT as an AI-assisted tool for statistical analysis: A comparative study with SPSSIntelligent Data Analysis · Mon,

More from Intelligent Data Analysis

Enhancing pedestrian detection accuracy: A full-stage refined proposal algorithm for false positive suppressionMon,
Hybrid deep transfer learning framework for cross-domain explainable ICS intrusion detectionFri,
Three-dimensional information extraction method of wire end for live-line working robots in strong illumination environmentsSat,
CRISPR dependency profiles distinguish pediatric from adult cancer cell lines via explainable machine learning: Identification of GPX4 and proliferative genes as therapeutic targetsThu,
A structural framework for instance-specific dynamic selection in classifier ensemblesThu,