filter_missing_values: Drop the Missing Values Above a Certain Threshold
In mrbakhsh/HPiP: Host-Pathogen Interaction Prediction
View source: R/filter_missing_values.R
filter_missing_values R Documentation
Drop the Missing Values Above a Certain Threshold
Description
Given an input matrix, compute the missingness rate for
each features and keep only features with missing rate more than
user-defined percentage.
Usage
filter_missing_values(x, max_miss_rate = 20)
Arguments
x
A numeric matrix as input.
max_miss_rate
Maximal missing rate allowed for a feature;default
is 20.
Details
filter_missing_values
Value
A dataframe with features with missingness rate of more than
user-defined threshold.
Author(s)
Matineh Rahmatbakhsh, matinerb.94@gmail.com
Examples
x <- matrix(1:10, ncol = 2)
x[, 2] <- NA
filter_missing_values(x, 30)
mrbakhsh/HPiP documentation built on March 28, 2023, 4:35 p.m.
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View source: R/filter_missing_values.R
| filter_missing_values | R Documentation |
Drop the Missing Values Above a Certain Threshold
Description
Given an input matrix, compute the missingness rate for each features and keep only features with missing rate more than user-defined percentage.
Usage
filter_missing_values(x, max_miss_rate = 20)
Arguments
x |
A numeric matrix as input. |
max_miss_rate |
Maximal missing rate allowed for a feature;default is 20. |
Details
filter_missing_values
Value
A dataframe with features with missingness rate of more than user-defined threshold.
Author(s)
Matineh Rahmatbakhsh, matinerb.94@gmail.com
Examples
x <- matrix(1:10, ncol = 2)
x[, 2] <- NA
filter_missing_values(x, 30)
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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