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Each segment should take an arbitrary number of linear predictors. As with the `segmented` package, the only requirement is that one continuous predictor (say, `x`) is the dimension of the change poin…
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Todo:
- [x] Create a blanc `Variant` page
- Header
- [x] Entity id
- [x] external ref
- [x] Left column metadata
- Location
- Insilico predictors
- [x] Population column
- POC visuali…
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The documentation doesn't specify what to do with the result of `optimize_signature`
The code specifies that it should return a dspy.Program:
https://github.com/stanfordnlp/dspy/blob/303c66991899a7f…
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In some applications the predictors are monotonic and it does not make sense to have more than one split on a predictor. Suggest having an option to limit trees to a single split.
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How to handle this? lm includes data, which can be standardized and the model re-run. Other model objects do not include data.
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When simulating predictors, squidSim allows to specify the covariance matrix between all these predictors. squidSim also allows to input the user data. However, the covariance between simulated and kn…
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Predictors for all other models are provided, but not this one https://huggingface.co/PowerInfer?search_models=predictor
I was wanting to convert TurboSparse-Mixtral into a quantized GGUF to reprod…
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In the previous exercises, we used a quantitative predictor in our linear regression, but it's important to note that we can also use categorical predictors. The simplest case of a categorical predict…
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Hi! Thanks for this cool package! Maybe I missed something, but would it also be possible to define features on the level of species in addition to, for example, environmental and spatial features?
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### What happened + What you expected to happen
Is it possible in Nixtla to use the predict method to extend the forecasting over the whole test set length? e.g. train a NeuralForecast model to predi…