AAAI Publications, Twenty-Third International FLAIRS Conference

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CsMTL MLP For WEKA: Neural Network Learning with Inductive Transfer
Liangliang Tu, Benjamin Fowler, Daniel L. Silver

Last modified: 2010-05-06


We present context-sensitive Multiple Task Learning, or csMTL, as a method of inductive transfer embedded in the well known WEKA machine learning suite. csMTL uses a single output neural network and additional contextual inputs for learning multiple tasks. Inductive transfer occurs from secondary tasks to the model for the primary task so as to improve its predictive performance. The WEKA multi-layer perceptron algorithm is modified to accept csMTL encoded multiple tasks examples. Testing on three domains of tasks demonstrates that this WEKA-based version of csMTL provides modest but beneficial performance increases. Our on-going objective is to increase the availability of transfer learning systems to students, researchers and practitioners.


transfer learning, inductive transfer, WEKA, neural networks, multilayer perceptron, machine lifelong learning

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