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*Context*: see https://github.com/rust-ml/discussion/issues/1.
This is meant to be a list of functionality we want to implement (a roadmap?) - I have refrained from including more sophisticated met…
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1. Introduction
- Business problem: Forecast bike demand. Up to t+28. 28 hours ahead would allow us to generate a forecast at 8pm for the entire next day. 8pm represents the last period of sustai…
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Hi there!
Thanks for the package. Am I missing something (I did search the help files) or does naniar not have functions for imputing categorical data?
If no methods for categorical data are ava…
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The file `R/phasingImpute4.R` has the comment
`## impute for chrX PAR >> with an additional flag: --Xpar.`
However, the lines following it and running IMPUTE4 do not have that flag set, i.e.
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Current package impute missing values using mean and median.
Now I have identified an approach to apply Machine Learning models for imputing the missing values:
**Existing approach**:
Impute mi…
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This awesome function takes `nominal` or `numeric` params.
Ordinal type cols fall between `nominal` and `numeric` and it isn't clear to the user which to use (since behavior changes from knn to bag).…
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For the same data, when I work with a smaller number of cells (1000), it works fine. But when I'm working with a lot more cells (>50000),The flux and balance files are NA.Why is that?
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Add the ability to "fix" some data quality issues and return a fixed dataframe. Example, removing duplicates or removing whitespace etc.
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As a follow-up to https://github.com/reconhub/i2extras/issues/7 it would be useful to have a procedure for replacing NAs in an *incidence2* object. Different methods could be foreseen, e.g.:
* usin…
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I received the following question by email*
> Dear Romain
>
> thanks for this toolkit. Can TSlearn handle missing data - quite a big problem in time series analysis of Earth Observation (EO) dat…