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I get two errors in the Day2 Rmd file.
The first occurs at around line 694 with this line of code:
`plot_predict_interaction(forest, BreastCancer_train[,-c(10)], "Cell.size", "Cl.thickness")`
wh…
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Hi all,
I was just reflecting on miceforest's imputation strategy, and I wonder if it may underestimate uncertainty in missing values.
In classical multiple imputation methods that use a Gaussia…
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Observed in #14330: the IterativeImputer doesn't converge, as a matter of fact, the convergence criterion doesn't seem to go down with iterations.
To me that indicates that either there's an issue wi…
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Great package, I find it very useful for imputation and a lot better than many alternative methods. What do you think about changing the random forest engine from "randomForest" to one of the newer pa…
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Dear author,
In your introduction, the categorical features need to be one-hot format.
Could you please provide an example to explain it?
Because, I'm not sure how to work on several categori…
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In multivariate imputation, we estimate the values of missing data using regression or classification models based of the other variables in the data.
The iterativeimputer will allows us only to us…
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A interesting added feature could be functionality for exploring potential data biases of analytical datasets.
- taxonomic biases (ie calculate taxonomic distinctness of subsets of complete case speci…
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I know there is a parameter for maximum iterations. But what about something to control when convergence has been reached?
What is the convergence criterion anyway? I have been testing this on some s…
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@GaelVaroquaux points out that iterative imputation with a regularised least-squares model is more-or-less the same as using NMF for imputation. We should instead use RandomForestRegressor as the defa…