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» A Machine Learning Approach to TCP Throughput Prediction
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COLCOM
2005
IEEE
14 years 2 months ago
Developing a framework for integrating prior problem solving and knowledge sharing histories of a group to predict future group
Using a combination of machine learning probabilistic tools, we have shown that some chemistry students fail to develop productive problem solving strategies through practice alon...
Ron Stevens, Amy Soller, Alessandra Giordani, Luca...
KAIS
2010
144views more  KAIS 2010»
13 years 7 months ago
Boosting support vector machines for imbalanced data sets
Real world data mining applications must address the issue of learning from imbalanced data sets. The problem occurs when the number of instances in one class greatly outnumbers t...
Benjamin X. Wang, Nathalie Japkowicz
MLDM
2005
Springer
14 years 2 months ago
A Grouping Method for Categorical Attributes Having Very Large Number of Values
In supervised machine learning, the partitioning of the values (also called grouping) of a categorical attribute aims at constructing a new synthetic attribute which keeps the info...
Marc Boullé
BMCBI
2004
112views more  BMCBI 2004»
13 years 8 months ago
Predicting co-complexed protein pairs using genomic and proteomic data integration
Background: Identifying all protein-protein interactions in an organism is a major objective of proteomics. A related goal is to know which protein pairs are present in the same p...
Lan V. Zhang, Sharyl L. Wong, Oliver D. King, Fred...
CEC
2009
IEEE
14 years 3 months ago
Evolving hypernetwork models of binary time series for forecasting price movements on stock markets
— The paper proposes a hypernetwork-based method for stock market prediction through a binary time series problem. Hypernetworks are a random hypergraph structure of higher-order...
Elena Bautu, Sun Kim, Andrei Bautu, Henri Luchian,...