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JCP
2008
166views more  JCP 2008»
13 years 8 months ago
Water Demand Prediction using Artificial Neural Networks and Support Vector Regression
Computational Intelligence techniques have been proposed as an efficient tool for modeling and forecasting in recent years and in various applications. Water is a basic need and as...
Ishmael S. Msiza, Fulufhelo Vincent Nelwamondo, Ts...
CORR
2002
Springer
96views Education» more  CORR 2002»
13 years 7 months ago
Thumbs up? Sentiment Classification using Machine Learning Techniques
We consider the problem of classifying documents not by topic, but by overall sentiment, e.g., determining whether a review is positive or negative. Using movie reviews as data, w...
Bo Pang, Lillian Lee, Shivakumar Vaithyanathan
BMCBI
2008
141views more  BMCBI 2008»
13 years 8 months ago
MiRTif: a support vector machine-based microRNA target interaction filter
Background: MicroRNAs (miRNAs) are a set of small non-coding RNAs serving as important negative gene regulators. In animals, miRNAs turn down protein translation by binding to the...
Yuchen Yang, Yu-Ping Wang, Kuo-Bin Li
MLMI
2005
Springer
14 years 1 months ago
Dominance Detection in Meetings Using Easily Obtainable Features
We show that, using a Support Vector Machine classifier, it is possible to determine with a 75% success rate who dominated a particular meeting on the basis of a few basic feature...
Rutger Rienks, Dirk Heylen
SEAL
2010
Springer
13 years 5 months ago
Dominance-Based Pareto-Surrogate for Multi-Objective Optimization
Abstract. Mainstream surrogate approaches for multi-objective problems build one approximation for each objective. Mono-surrogate approaches instead aim at characterizing the Paret...
Ilya Loshchilov, Marc Schoenauer, Michèle S...