Dealing with Missing Data in R
Автор: LiquidBrain Bioinformatics
Загружено: 2022-06-03
Просмотров: 7229
Data imputation is a technique that allows missing data to be replaced with data without affecting the trend of the analysis. It can be done in a huge numbers of ways. In R there's a lot of package that could allow the imputation of data easily as long as you understand the method you desire and why you are running on such method. IN this video I want to show case how you can use the mice package to easily replace data in a matrix and how you can compare the performance of each algorithm using ggplot2.
Slides
https://docs.google.com/presentation/...
Github
https://github.com/brandonyph/Imputat...
Email: liquidbrain.r@gmail.com
Website: https://www.liquidbrain.org/videos
Patreon: / liquidbrain
Chapters
0:00 Introduction
1:05 What's imputation
1:45 Types of missing data
3:22 Measuring success
3:55 A number of different imputation techniques
9:05 R Script: introduction of the rmd format
10:06 Mean Imputation
11:40 locf and nocb
14:36 kNN and kNN imputation
19:00 Advance imputation with mice()
23:00 How does pmm and rf performed?
25:07 TCGA data Imputation
30:13 Effectiveness of Imputation
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