README.md

R-project

Machine Learning in R

Involve:

• Implemention :

KNN from Scratch; Stochastic Gradient Descent from Scracth; 3 layer Backpropogation Neural Network from Scracth;

• Application and Mathmatical Proof

1. Linear Regression

2. Guassian Discriminant Analysis/ Linear Discriminant Analysis

3. LASSO regression and Ridge regression

4. Tree based models( Random Forest/xgboost)

5. WordEmbedding - Word2Vec

Old Faithful data manipulation project

regex expression /rmd report/ rmd latex

see the report here

shiny

It's a visualization project to visualize the time series data of australia weather and spatial map visualization from 2013 to 2017. publish at shinyaap.io changshen

multivariate time series（Sydney Weather Forecasting）

1.The presentation slide available at here

2. The proposal and report

3. code for data manipulation and modelling(to be uploaded)

Data Manipulation

Use advanced R to conduct data manipulation and anlysis

1.Clinical Data

including the database join(merge),cleaning, format standardization(from SAS to R), group and summarize

Myfunction

list some of the simple functions I write for statistical computing or visualization

1. Emprical Power

2. Visualization of output of Emperical power

Example

N <- c(100, 200, 300)
alpha <- .01
sd <- 5
delta <- seq(0.5, 5, 0.5)
mu1 <- 5
power.1<-Emperical.power(N, alpha, sd,delta,mu1)
View(power.1)
plot.emperical.power(power.1)

N <- c(20, 40)
alpha <- c(.05, .10)
sd <- c(0.5,1)
delta <- seq(0.1, 1, 0.1)
mu1 <- 2
power.2<-Emperical.power(N, alpha, sd,delta,mu1)
View(power.2)
plot.emperical.power(power.2)

3. stratified

a function for stratified randomization for a two-arm study Example: returned a list include stratified randomized data set, seed, distribution summary

testa <- stratified(t=2, s=4, samplesize = 100, equal = TRUE, seed = 89676);testa
testb <- stratified(t=3, s=3, samplesize = c(80, 70, 50), equal = FALSE, seed = 124589);testb
testc <- stratified(t=5, s=3, samplesize = 60, equal = TRUE, seed = 907563);testc

Daxing Population Analysis

the Map Visualization of Anaysis is as follows