Suppose we are trying to model a classification problem with two labels: 'sick' and 'healthy. For the purpose of this test, we consider a positive result to be testing sick and a negative to test as healthy. After fitting the model with LDA in R, we compare predicted values from the actual values, as shown below: > lda.fit = lda(test.result ~ x1 + x2, data=mydata) predict (1da.fit) > lda. pred > lda.class=lda.pred$class > table (lda.class, mydata$test.result) = mydata lda.pred sick healthy sick 40 healthy 25 32 121

Suppose we are trying to model a classification problem with two labels: 'sick' and 'healthy. For the purpose of this test, we consider a positive result to be testing sick and a negative to test as healthy. After fitting the model with LDA in R, we compare predicted values from the actual values, as shown below: > lda.fit = lda(test.result ~ x1 + x2, data=mydata) predict (1da.fit) > lda. pred > lda.class=lda.pred$class > table (lda.class, mydata$test.result) = mydata lda.pred sick healthy sick 40 healthy 25 32 121

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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