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Currently the way that the penalized fit is built prohibits using the packages optional logistic regression because the fit function fixes the `model` parameter of `penalized::penalized()` at `'linear…
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Hello!
I was replicating one of the examples from the vignette on `predictnl` that you sent me, and I couldn't reproduce the example with the linear regression model:
``` r
library(rstpm2)
#> Lo…
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Running parallel eps-regression using caret and e1071 has worked fine for me in the past but am now getting an error:
```
Something is wrong; all the RMSE metric values are missing:
RMSE …
zdb88 updated
6 years ago
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This is a follow up to issue #870. `caret::train` is gobbling up memory to exhaustion with a 2 GB regression matrix, which I initially thought was cased by the number of sub-processes it triggers (tak…
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Function-valued regression where either the response or one of the predictor variables is a function has a variety of applications. Classic examples are fMRI data as a functional response, and charact…
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Hello,
I discovered the following issue:
By default this runs smoothly
~~~r
library(papaja)
load('.../mixed_data.rdata')
recall_anova
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Hello,
I'm trying to train a multi layer perceptron for non linear regression on a dataset but it keeps giving me this error :
Warning message:
In nominalTrainWorkflow(x = x, y …
ghost updated
6 years ago
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i\It would be awesome if the program could also generate a formula which represents the graph.
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From a user: It's working fine most of the time but sometimes I get this error using:
plotSimulatedResiduals
Error in qrnn::qrnn.fit(x = as.matrix(pred), y = as.matrix(res), n.hidden = 4, :
…
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I'm using statsmodels' MixedLM a lot recently, and some of the data I am working with is becoming quirkier and quirkier. I am wondering whether any of the following data wold be inappropriate for the …