Foundry

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Boosted decision trees should fit well into the Foundry learning package. It should also support the stochastic variant.

jbasilico

A good implementation of a basic restrictions boltzmann machine (RBM) would be a good addition to the Foundry. It could then be used as a feature transformation for further learning.

jbasilico

A common task in both the Foundry (and more generally) is to keep track of some values and assign values unique indices. These indices are typically integers starting from 0,...

jbasilico

A common step in learning is to do feature normalization. One popular method for doing this is to normalize each feature by mapping it to a standard normal (Gaussian) distribution...

jbasilico

There should be a simple static method and associated batch learner for doing simple univariate regression where there is a single input and a single output. This is the basic...

jbasilico

Random projections of the input data can be a useful method for creating non-linear features. It conceptually fits nicely with the rest of the Foundry, so we should add support...

jbasilico

The dot product is happening in the wrong order for spherical k-means (cosine distance), which causes a loop over the dense vector. It should be over the sparse one. One...

jbasilico

It doesn't seem like sparse vector times dense matrix is working at an appropriate speed. Neither is dense matrix times sparse vector.

jbasilico

It would be nice to be able to apply optimization methods to learn logistic regression type functions. For some background, see the forum post: http://www.cognitivefoundry.org/?topic=a-couple-of-usage-questions-learning-package

jbasilico

Our optimization methods for learning are currently designed with a very heavy bias towards being used with a supervised cost function. However, there are other types of cost functions that...

jbasilico