[FRIAM] Weighted Ensemble

[Roger Frye]

Yes, I have been using the sklearn random forest and other ensemble methods
at SigmaLabsInc. I can't tell you too much because it is proprietary, but
we downsample the normal pixels some, upsample the anomalies some, and
apply class weights to complete the balance.

We wrote a white paper that is available here
https://sigmalabsinc.com/machine-learning-a-game-changer-for-additive-manufacturing/


On Sun, Aug 29, 2021 at 2:08 PM Jon Zingale <jonzingale at gmail.com> wrote:

> I am presently working on learning weighted ensemble
> <https://arxiv.org/pdf/1906.00856.pdf> sampling techniques and was
> curious if any here have worked with them before. The technique seems
> promising and has enjoyed quite a bit of success (even above MCMC
> <https://en.wikipedia.org/wiki/Markov_chain_Monte_Carlo>) in circles
> concerned with reaction rates for rare events.
>
> Some points of interest for me include:
>
>    1. A better sampling of fringe-outlier works/art from streaming
>    services.
>    2. An alternative (bin-based sampling) to globally defined "fitness"
>    measures in evolutionary modeling.
>    3. An application of diffusion-limited aggregation to general search
>    (especially in the face of limited resources)
>    4. An application of linear logic to optimization problems in conformation
>    prediction <https://en.wikipedia.org/wiki/Protein_structure_prediction>
>    .
>    5. Investigation of dynamical properties, such as distribution of
>    trajectories with "high winding number", on strange attractors.
>
>
> While I am just beginning to grok the technique, I thought it might be
> fruitful to ask here.
>
> Jon
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