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ML
2000
ACM
185views Machine Learning» more  ML 2000»
14 years 9 months ago
A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty-Three Old and New Classification Algorithms
Twenty-two decision tree, nine statistical, and two neural network algorithms are compared on thirty-two datasets in terms of classification accuracy, training time, and (in the ca...
Tjen-Sien Lim, Wei-Yin Loh, Yu-Shan Shih
HIS
2008
14 years 11 months ago
REPMAC: A New Hybrid Approach to Highly Imbalanced Classification Problems
The class imbalance problem (when one of the classes has much less samples than the others) is of great importance in machine learning, because it corresponds to many critical app...
Hernán Ahumada, Guillermo L. Grinblat, Luca...
CVPR
2010
IEEE
15 years 6 months ago
The Role of Features, Algorithms and Data in Visual Recognition
There are many computer vision algorithms developed for visual (scene and object) recognition. Some systems focus on involved learning algorithms, some leverage millions of trainin...
Devi Parikh and C. Lawrence Zitnick
MLG
2007
Springer
15 years 3 months ago
Graphs, Hypergraphs, and Inductive Logic Programming
Abstract. There are many connections between graph mining and inductive logic programming (ILP), or more generally relational learning. Up till now these connections have mostly be...
Hendrik Blockeel, Tijn Witsenburg, Joost N. Kok
SDM
2008
SIAM
157views Data Mining» more  SDM 2008»
14 years 11 months ago
ROC-tree: A Novel Decision Tree Induction Algorithm Based on Receiver Operating Characteristics to Classify Gene Expression Data
Gene expression information from microarray experiments is a primary form of data for biological analysis and can offer insights into disease processes and cellular behaviour. Suc...
M. Maruf Hossain, Md. Rafiul Hassan, James Bailey