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KDD
1998
ACM
120views Data Mining» more  KDD 1998»
15 years 8 months ago
Large Datasets Lead to Overly Complex Models: An Explanation and a Solution
This paper explores unexpected results that lie at the intersection of two common themes in the KDD community: large datasets and the goal of building compact models. Experiments ...
Tim Oates, David Jensen
DOCENG
2007
ACM
15 years 7 months ago
Adapting associative classification to text categorization
Associative classification, which originates from numerical data mining, has been applied to deal with text data recently. Text data is firstly digitalized to database of transact...
Baoli Li, Neha Sugandh, Ernest V. Garcia, Ashwin R...
108
Voted
INCDM
2010
Springer
152views Data Mining» more  INCDM 2010»
15 years 7 months ago
The Impact of Experimental Setup on Prepaid Churn Modeling: Data, Population and Outcome Definition
Prepaid customers in mobile telecommunications are not bound by a contract and can therefore change operators (‘churn’) at their convenience and without notification. This make...
Dejan Radosavljevik, Peter van der Putten, Kim Kyl...
KDD
2010
ACM
224views Data Mining» more  KDD 2010»
15 years 7 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
PAKDD
2000
ACM
161views Data Mining» more  PAKDD 2000»
15 years 7 months ago
Adaptive Boosting for Spatial Functions with Unstable Driving Attributes
Combining multiple global models (e.g. back-propagation based neural networks) is an effective technique for improving classification accuracy by reducing a variance through manipu...
Aleksandar Lazarevic, Tim Fiez, Zoran Obradovic