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could be random forests, boosted regression trees, or similar
would have the benefit of considering interactions among explanatory variables more effectively
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I have a graph that was built with Seqwish and augmented with reads mapped with GraphAligner. I used vg version 1.16.0 to build an xg for the augmented graph
```
vg index -x graph.aug.xg graph.aug.v…
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# Endowments
In MPSGE there is syntax of the form
```
e: E q:Q r:RATE
```
This is equivalent to
```
e: E q:Q*RATE
```
We should add a keyword to the endowment constructor of the fo…
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Hi! I am a newbie in GAM. It would be great to add in these tutorials how to do bootstrapping. Also include on how to generate plots with bootstrapped CI. Thank you
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Would it be possible by any chance for investr to also support scam (https://cran.r-project.org/web/packages/scam/index.html) and mgcv::gam (https://cran.r-project.org/web/packages/mgcv/index.html) mo…
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Hello! Thanks for this package, it's so great!
I have a question about GAMs with mgcv.
I wonder if there is a function to programmatically find variables based on smooth term strings (without ha…
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This issue would address potential solve speedups (e.g., I am seeing week-long solve times at the moment for some scenarios).
The idea is straightforward - for a scenario which has a solution, prov…
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# Modelgam Project Roadmap - MVP
- [X] Create Package Structure
- [ ] Develop MVP Algorithms (#2) - Get basic use-cases from business-science/modeltime#71, Test on several datasets
- [ ] Develop R…
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Develop `gen_additive_mod()` algorithm with modes "regression" and "classification"
- Use `parsnip::linear_reg()` as an example.
- Linear Reg: https://github.com/tidymodels/parsnip/blob/maste…
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using the approach laid out in:
https://github.com/dswah/pyGAM/issues/154
dswah updated
6 years ago