# fig8_1

## PURPOSE

Local Regression and Likelihood, Figure 8.1.

## SYNOPSIS

This is a script file.

## DESCRIPTION

     Local Regression and Likelihood, Figure 8.1.

     Discrimination/Classification, simple example using
     logistic regression.

     Author: Catherine Loader

     NEED: level=0.5 for contour plot.

## CROSS-REFERENCE INFORMATION

This function calls:

- fitted Fitted values from a locfit object.
- lfplot Plot (for one or two dimensions) a locfit() fit.
- locfit Smoothing noisy data using Local Regression and Likelihood.
- predict Interpolate a fit produced by locfit().

This function is called by:

- runbook

## SOURCE CODE

    0001 % Local Regression and Likelihood, Figure 8.1.
    0002 %
    0003 % Discrimination/Classification, simple example using
    0004 % logistic regression.
    0005 %
    0006 % Author: Catherine Loader
    0007 %
    0008 % NEED: level=0.5 for contour plot.
    0009
    0010 load cltrain;
    0011 fit = locfit([x1 x2],y,'family','binomial','scale',0);
    0012 figure('Name','fig8_1: logistic regression');
    0013 lfplot(fit,'contour');
    0014 hold on;
    0015 u = find(y==0);
    0016 plot(x1(u),x2(u),'.');
    0017 u = find(y==1);
    0018 plot(x1(u),x2(u),'.','color','red');
    0019 hold off;
    0020
    0021 py = fitted(fit)>0.5;
    0022 disp('Classification table for training data');
    0023 tabulate(10*y+py);
    0024
    0025 load cltest;
    0026 py = predict(fit,[x1 x2])>0;
    0027 disp('Classification table for test data');
    0028 tabulate(10*y+py);