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» Phenomenal Data Mining: From Data to Phenomena
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KDD
2010
ACM
224views Data Mining» more  KDD 2010»
15 years 5 months ago
Multi-label learning by exploiting label dependency
In multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for the unseen example. Due to the tremendous (ex...
Min-Ling Zhang, Kun Zhang
AUSDM
2006
Springer
114views Data Mining» more  AUSDM 2006»
15 years 5 months ago
Consolidated Trees: An Analysis of Structural Convergence
When different subsamples of the same data set are used to induce classification trees, the structure of the built classifiers is very different. The stability of the structure of ...
Jesús M. Pérez, Javier Muguerza, Ola...
AUSDM
2008
Springer
258views Data Mining» more  AUSDM 2008»
15 years 3 months ago
wFDT - Weighted Fuzzy Decision Trees for Prognosis of Breast Cancer Survivability
Accurate and less invasive personalized predictive medicine can spare many breast cancer patients from receiving complex surgical biopsies, unnecessary adjuvant treatments and its...
Umer Khan, Hyunjung Shin, Jongpill Choi, Minkoo Ki...
122
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SDM
2008
SIAM
139views Data Mining» more  SDM 2008»
15 years 3 months ago
Maximal Quasi-Bicliques with Balanced Noise Tolerance: Concepts and Co-clustering Applications
The rigid all-versus-all adjacency required by a maximal biclique for its two vertex sets is extremely vulnerable to missing data. In the past, several types of quasi-bicliques ha...
Jinyan Li, Kelvin Sim, Guimei Liu, Limsoon Wong
CLEIEJ
2004
168views more  CLEIEJ 2004»
15 years 1 months ago
Contributions of KDD to the Knowledge Management Process: a Case Study
Knowledge Discovery in Databases (KDD), as any organizational process, is carried out beneath a Knowledge Management (KM) model adopted (even informally) by a corporation. KDD is ...
Paulo de Tarso Costa de Sousa, Hércules Ant...