Multi-agent approach for data mining-based bagging ensembles to improve the decision process for big data.
Ahmed GhenabziaOkba KazarAbdelhak MerizigZaoui SayahMerouane ZoubeidiPublished in: Int. J. Inf. Commun. Technol. (2020)
Keyphrases
- big data
- decision process
- data mining
- data science
- multi agent
- data analysis
- decision making
- knowledge discovery
- decision support
- data visualization
- ensemble methods
- business intelligence
- data warehousing
- data stores
- massive datasets
- big data analytics
- machine learning
- cloud computing
- data management
- data analytics
- predictive modeling
- decision trees
- decision makers
- ensemble learning
- random forests
- decision support system
- massive data
- decision processes
- social media
- health informatics
- unstructured data
- base classifiers
- data processing
- data intensive computing
- data mining methods
- ensemble selection
- vast amounts of data
- statistical learning
- ensemble classifier
- imbalanced data
- data warehouse
- data mining applications
- information retrieval
- data mining techniques
- neural network ensembles
- artificial intelligence
- statistical data mining
- ensemble members
- training set
- classifier ensemble
- query language
- text mining