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Momo2019

Vu Thien

Recently Published

CVD - Table 1 & codes
CVD - Table 1
Decision Tree - Regression
Outliners checking (3) using KNN
Outliners checking (2)
Outliners checking
Calculate the best threshold (blood glucose cut-off)
2024-06-05 Naive Bayes
Logistic Regression - ML for DD project
LR - ML study
Lasso 2
Lasso Regression
Imputation methods
Nutrition
Nutri and DD
DD3
DD project - 20231201
DD Project (cont.)
DD Project
Data 2013-2014 (cont.)
Data 2013-2014
Exer 3: Learning schedule
Exer 2: Thomas Edison
List of websites
Uploading pictures with Rmarkdown
Markdown KHTN
Time series analysis for Incident CHD prediction (S dat)
Panel analyis
Visualization - Gapminder dataset
Spagetti graph for panel data
Basic 4 - Visualization with obesity data
Basic 3 - Visualization for gapminder data set
Basic 2 - ggplot2
Basic 1
SUMS - Framingham - Nomogram for Stroke prediction
SUMS - Framingham - Visualizing
ggplot2 - cont 2.
http://www.sthda.com/english/wiki/be-awesome-in-ggplot2-a-practical-guide-to-be-highly-effective-r-software-and-data-visualization
SUMS - Logistic Regression - Plot Forest
ggplot2 - cont
ggplot2
SUMS - Linear Regression
ML - Preprocessing - Down sampling - Visualizing for Su data
ML- Logistic Regression for Titanic
Machine Learning & unbalace data set
ML - Logistic Regression
ML - Linear Regression online
ML - LR online
Table 1 Full
Important and applicable
ICAS project and simulation
Simulation - Discordance - Percentiles
Data pre-processing
2nd day of R class
SUMS 03 - Random Forest Plot
Select and Rename with library(dplyr)
Logic and If
Basic Mathematics (cont. 2)
Basic Mathematics (cont. 1)
Simulation data set
SUMS 04 - ggplot2, tidyverse
SUMS 02 - Import, check normal, parametric test
SUMS 02 - R build in functions
SUMS 01 - Simple calculation
Supervised ML - RF
Random Forest - For Stroke prediction
Calculate confidence interval
Summary - Correlation coefficients
Academic presentation - Jan 2023
Prediction Model
CKD and Stroke, or Stroke prediction model
Self-study 02
Nomogram
Self-study 01
R learning
Practice day 2