CsMTL MLP For WEKA: Neural Network Learning with Inductive Transfer

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 thisWEKA-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.