MEKA: A Multi-label/Multi-target Extension to WEKA

被引：0

作者：

Read, Jesse ^{[1
,2
]}

Reutemann, Peter ^{[3
]}

Pfahringer, Bernhard ^{[3
]}

Holmes, Geoff ^{[3
]}

机构：

[1] Aalto Univ, Espoo, Finland

[2] Aalto Univ, Dept Comp Sci, Espoo, Finland

[3] Univ Waikato, Dept Comp Sci, Hamilton, New Zealand

来源：

JOURNAL OF MACHINE LEARNING RESEARCH | 2016年 / 17卷

关键词：

classification; learning; multi-label; multi-target; incremental;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Multi-label classification has rapidly attracted interest in the machine learning literature, and there are now a large number and considerable variety of methods for this type of learning. We present MEKA : an open-source Java framework based on the well-known WEKA library. MEKA provides interfaces to facilitate practical application, and a wealth of multi-label classifiers, evaluation metrics, and tools for multi-label experiments and development. It supports multi-label and multi-target data, including in incremental and semi-supervised contexts.

引用

页数：5

共 50 条

[1] Multi-label Classification via Multi-target Regression on Data Streams
Osojnik, Aljaz
Panov, Pance
Dzeroski, Saso
DISCOVERY SCIENCE, DS 2015, 2015, 9356 : 170 - 185
[2] PSTG-based multi-label optimization for multi-target tracking
Chen, Jiahui
Sheng, Hao
Li, Chao
Xiong, Zhang
COMPUTER VISION AND IMAGE UNDERSTANDING, 2016, 144 : 217 - 227
[3] Multi-label classification via multi-target regression on data streams
Osojnik, Aljaz
Panov, Pance
Dzeroski, Saso
MACHINE LEARNING, 2017, 106 (06) : 745 - 770
[4] Multi-label classification via multi-target regression on data streams
Aljaž Osojnik
Panče Panov
Sašo Džeroski
Machine Learning, 2017, 106 : 745 - 770
[5] Classification on Grade, Price, and Region with Multi-Label and Multi-Target Methods in Wineinformatics
James Palmer
Victor S.Sheng
Travis Atkison
Bernard Chen
Big Data Mining and Analytics, 2020, 3 (01) : 1 - 12
[6] Multi-label and Multi-target Sampling of Machine Annotation for Computational Stance Detection
Liu, Zhengyuan
Chieu, Hai Leong
Chen, Nancy F.
FINDINGS OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS - EMNLP 2023, 2023, : 2641 - 2649
[7] Multi-Target Core Network-based Networked Multi-label Classification
Li, Lei
Zhang, Fang
Ma, Di
Zhou, Chuan
Hu, Xuegang
2018 9TH IEEE INTERNATIONAL CONFERENCE ON BIG KNOWLEDGE (ICBK), 2018, : 274 - 281
[8] Multi-Label Attribute Reduction Based on Neighborhood Multi-Target Rough Sets
Zheng, Wenbin
Li, Jinjin
Liao, Shujiao
Lin, Yidong
SYMMETRY-BASEL, 2022, 14 (08):
[9] Classification on Grade, Price, and Region with Multi-Label and Multi-Target Methods in Wineinformatics
Palmer, James
Sheng, Victor S.
Atkison, Travis
Chen, Bernard
BIG DATA MINING AND ANALYTICS, 2020, 3 (01): : 1 - 12
[10] Multi-Label Classification Using Deep Belief Networks for Virtual Screening of Multi-Target Drug
Fitriawan, Aries
Wasito, Ito
Syafiandini, Arida Ferti
Amien, Mukhlis
Yanuar, Arry
2016 INTERNATIONAL CONFERENCE ON COMPUTER, CONTROL, INFORMATICS, AND ITS APPLICATIONS (IC3INA) - RECENT PROGRESS IN COMPUTER, CONTROL, AND INFORMATICS FOR DATA SCIENCE, 2016, : 102 - 107

← 1 2 3 4 5 →