lasso_by_coordinate_descent.Rmd

---
title: "LASSO by coordinate descent method"
author: "Kenji Kondo"
date: "2019/8/21"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

## Read Data

```{r}
library(MASS)
xy <- Boston # xy is a data.frame to be processed.
colnames(xy)[ncol(xy)] <- "y" # Let medv be the objective variable, y.

## Split data into train and test
n <- nrow(xy) # Sample size.
set.seed(2018) # For reproducibility.
test.id <- sample(n, round(n/4)) # ID numbders for test data.
test <- xy[test.id,] # test is the data.frame for testing.
train <- xy[-test.id,] # train is the data.frame for training.
x <- as.matrix(train[-ncol(xy)])
y <- train$y
newx <- as.matrix(test[-ncol(xy)])
y_true <- test$y
```

## LASSO by glmnet

```{r}
library(glmnet)
model <- glmnet(x, y, family="gaussian", alpha=1, lambda=0.5)  # alpha=1 is LASSO
print(model$beta)
```