encog-java-core
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jeffheaton
Task-balance (used in Workbench, for instance) produces unbalanced training and eval sets:  As depicted, `data_balance.csv` contains balanced ideal outputs (only two classes in this simplified example, i.e. y=0 or...
When training is run via Analyst (after clicking on .ega file), there is no graph plotting the current error and error improvement, in contrast to training run from BasicNetwork tab...
Hi, I am a happy user of Encog Framework. (version 3.0 beta) I have a request for a minor enhancement, in EncogPersistor interface you use Inputstream and OutputStream in read...
PMML
Have you thought about supporting PMML? This XML standard allows you to exchange predictive models with other applications and it is quite well supported now. That would allow for instance...
I think that in Encog 3 the notion of population already exists but it seems to be tied to genetic algorithms like the standard GA and Neat. The evolutionary and...
This is a feature request. It would be helpful to expose the parameters of the training algorithms with setters and getters. Take RProp for instance (TrainFlatNetworkResilient). Some of the parameters...
It would be nice to have an example of how to use the hopfield network for optimization problems. Example: TSP.
Now that Issue #28 has been added, it would be very nice to be able to add regularization, and other strategies to the workbench training. This should be added to...
Currently, SVMSearch performs something like two nested for loops and tries to find a combination of parameters that satisfies the required maximum error. While it uses constant steps for both...
Learning curves are a useful tool to detect the bias/variance problem. See "X. ADVICE FOR APPLYING MACHINE LEARNING - Learning Curves" (12 min) video at http://www.ml-class.org/course/video/preview_list for a thorough explanation.