# [R] Linear regression of 0/1 response ElemStatLearn (Fig. 2.1 the elements of statistical learning)

David L Carlson dcarlson at tamu.edu
Mon Sep 1 21:36:24 CEST 2014

```This is a list for R questions, not statistics or algebra, but if you set g=.5 and solve the linear model for x2 (ignore e), you will have your answer, eg:

.5 = B1 + B2*X1 + B3*X2

where B1, 2, 3 are the three coefficients of the linear model, coef()[1], [2], [3].

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David L Carlson
Department of Anthropology
Texas A&M University
College Station, TX 77840-4352

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf Of Denis Kazakiewicz
Sent: Monday, September 1, 2014 5:27 AM
To: r-help at r-project.org
Subject: [R] Linear regression of 0/1 response ElemStatLearn (Fig. 2.1 the elements of statistical learning)

Hello
In chapter 2 ESL book authors write: Let's look at example of linear
model in a classification context
They fit a simple linear model g = 0.3290614 -0.0226360x1 + 0.2495983x2 + e,
where g is given with values 0 or 1. Then they made a decision boundary
where yhat, if yhat>0.5 then yellow.

Question: There is a separation line on the x1x2 plot. Where did
intercept and slope for this line come from?

In the ElemStatLearn R package, they simply put as abline(
(0.5-coef(x.mod)[1]
<http://i.stack.imgur.com/ANaTc.png>)/coef(x.mod)[3],
-coef(x.mod)[2]/coef(x.mod)[3]), where first term is the intercept, and
second term is slope for this line

Regards
Denis

```