inst/shiny-examples/NAimputation/NAimputation.md
In rsamantha/LCMSexplore: Demo for the EBI-EMBO Metabolomics Course 2018
Evaluating missing values and imputing strategies
This demo allows you to explore the RUBUS dataset (available from Metabolights with ID: MTBLS333). The dataset contains the untargeted measure of 13 red rubus samples and 12 yellow rubus samples.
Some question to orient your discussion ...
- What is the meaning of the plots?
- Is the imputation strategy affecting the data distribution?
- Is it important to consider class labels?
- Which is the best imputation strategy?
rsamantha/LCMSexplore documentation built on May 14, 2019, 10:31 p.m.
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Evaluating missing values and imputing strategies
This demo allows you to explore the RUBUS dataset (available from Metabolights with ID: MTBLS333). The dataset contains the untargeted measure of 13 red rubus samples and 12 yellow rubus samples.
Some question to orient your discussion ...
- What is the meaning of the plots?
- Is the imputation strategy affecting the data distribution?
- Is it important to consider class labels?
- Which is the best imputation strategy?
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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