Multi-label Classification Jesse Read Universidad Carlos III de Madrid. Department of Signal Theory and Communications Madrid, Spain

Source URL: jmread.github.io

Journal of Machine Learning ResearchSubmitted 8/13; PublishedPyStruct - Learning Structured Prediction in Python Andreas C. M¨

Source URL: amueller.github.io

• Machine learning
• Learning
• Artificial intelligence
• Structured prediction
• Graphical models
• Statistical classification
• Conditional random field
• Support vector machine
• Multi-label classification
• Gradient descent
• Convex optimization
• Mathematical optimization

WISE 2014 Challenge: Multi-label Classification of Print Media Articles to Topics Grigorios Tsoumakas1 , Apostolos Papadopoulos1, Weining Qian2 , Stavros Vologiannidis3 , Alexander D’yakonov4, Antti Puurula5 , Jesse Re

Source URL: perso.telecom-paristech.fr

• Machine learning
• Regression analysis
• Statistics
• Learning
• Artificial intelligence
• Estimation theory
• Statistical classification
• Data analysis
• Test set
• Linear regression
• Supervised learning
• Logistic regression

Kaggle WISE2014. 2nd-place Solution Team anttip: Antti Puurula(1) and Jesse ReadUniversity of Waikato, New Zealand (2) Aalto University and HIIT, Finland

Source URL: users.ics.aalto.fi

• Artificial intelligence
• Statistical classification
• Learning
• Machine learning
• Parts of speech
• Classifier chains
• Classifier
• Kaggle
• Multi-label classification
• Support vector machine
• Data

Synthetic Multi-label Data Streams Jesse Read, Bernhard Pfahringer, Geoff Holmes University of Waikato, Hamilton, New Zealand Feature Space Introduction

Source URL: jmread.github.io

• Machine learning
• Multi-label classification
• Concept drift
• Slashdot
• Artificial intelligence
• World Wide Web
• Learning

Classifier Chains for Multi-label Classification Jesse Read, Bernhard Pfahringer, Geoff Holmes, Eibe Frank Department of Computer Science The University of Waikato Hamilton, New Zealand {jmr30,bernhard,geoff,eibe}@cs.wai

Source URL: users.ics.aalto.fi

• Statistical classification
• Artificial intelligence
• Machine learning
• Learning
• Classifier chains
• Multi-label classification
• Multiclass classification
• Support vector machine
• Naive Bayes classifier
• AdaBoost
• Ensemble learning
• Boosting

Max-Margin Multiple-Instance Dictionary Learning Xinggang Wang† Baoyuan Wang‡

Source URL: pages.ucsd.edu

• Machine learning
• Artificial intelligence
• Learning
• Multiple instance learning
• Support vector machine
• Multiple-instance learning
• Conference on Computer Vision and Pattern Recognition
• Pattern recognition
• K-means clustering
• Multi-label classification
• Statistical classification
• Supervised learning

Classifier Chains for Multi-label Classification Jesse Read, Bernhard Pfahringer, Geoff Holmes, Eibe Frank University of Waikato, Hamilton, New Zealand Experiments Introduction

Source URL: jmread.github.io

• Statistical classification
• Classifier chains
• Machine learning
• Multi-label classification
• Ensemble learning
• Support vector machine
• Classifier
• K-nearest neighbors algorithm
• Information
• Cognition
• Computing

Advances in Multi-label Classification

Source URL: jmread.github.io

Multi-label Classification with Classifier Chains Jesse Read Aalto University School of Science, Department of Information and Computer Science and Helsinki Institute for Information Technology Helsinki, Finland

Source URL: jmread.github.io

• Classifier chains
• Multi-label classification
• Helsinki Institute for Information Technology
• Multiclass classification