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Everything about Ensemble learning
Statistics and machine learning technique
In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from any of the constituent learning algorithms alone. Unlike a statistical ensemble in statistical mechanics, which is usually infinite, a machine learning ensemble consists of only a concrete finite set of alternative models, but typically allows for much more flexible structure to exist among those alternatives. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Ensemble learningA 5-minute orientation
- Skim a recent paper: A Survey of Ensemble Learning: Concepts, Algorithms, Applications, and ProspectsInfluential work since 2022
- Pick up a classic book: Brecht registaThe most-reprinted book on the subject
- Read the landmark paper: Ensemble learning: A surveyCited 2,400 times
- Go sideways: Multi-label classificationA closely related topic
- Go sideways: Outline of machine learningA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🏆 Landmark papers (most cited)
Ensemble learning: A survey
Ensemble deep learning: A review
A survey on ensemble learning
Ensemble learning via negative correlation
Ensemble deep learning in bioinformatics
Domain Adaptive Ensemble Learning
Multistrategy ensemble learning: reducing error by combining ensemble learning techniques
Ensemble Based Extreme Learning Machine
🆕 Influential since 2022
A Survey of Ensemble Learning: Concepts, Algorithms, Applications, and Prospects
A comprehensive review on ensemble deep learning: Opportunities and challenges
Evolutionary bagging for ensemble learning
Cardiovascular Disease Detection using Ensemble Learning
Clustering ensemble via structured hypergraph learning
📚 Books worth reading
Brecht registaClaudio Meldolesi · 1989- 📕Brechts und Monks Urfaust-Inszenierung mit dem Berliner Ensemble 1952/53Bernd Mahl · 1986
- 📕First Book of the Piano (Usborne First Music)John C. Miles, Judy Tatchell · 1988
- 📕The Usborne First Book of the Recorder (Usborne First Music)Phillip Hawthorn, Jane Cook · 1987
- 📕Ensemble methodsZhou, Zhi-Hua Ph. D. · 2012
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- Multi-label classification In machine learning, multi-label classification or multi-output classification is a variant of the classification problem where multiple nonexclusive labels…
- Outline of machine learning The following outline is provided as an overview of, and topical guide to, machine learning: Machine learning (ML) is a subfield of artificial intelligence…
- Pattern recognition Pattern recognition is the task of assigning a class to an observation based on patterns extracted from data. While similar, pattern recognition (PR) is…
- Boosting (machine learning) In machine learning (ML), boosting is an ensemble learning method that combines a set of less accurate models (called "weak learners") to create a single…
- Statistical classification When classification is performed by a computer, statistical methods are normally used to develop the algorithm. Often, the individual observations are…
- Random forest Random forests or random decision forests is an ensemble learning method for classification, regression and other tasks that works by creating a multitude…
- Support vector machine In machine learning, a support vector machine (SVM) or support vector network is a supervised max-margin model with associated learning algorithms that…
- Supervised learning In machine learning, supervised learning (SL) is a type of machine learning paradigm where an algorithm learns to map input data to a specific output based…