5.1 3.8 Setosa 7.2 3.0 Virginica 5.4 3.4 Setosa 5.1 3.3 Setosa 5.4 3.9 Setosa 7.4 2.8 Virginica 6.1 2.8 Verscicolor

Case Studies In Health Information Management
3rd Edition
ISBN:9781337676908
Author:SCHNERING
Publisher:SCHNERING
Chapter7: Healthcare Statistics And Research Methods
Section: Chapter Questions
Problem 7.33.4C
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kindly provide me the solution of question given in attached image.

Consider the below given iris data set. This dataset contains 3 classes of 15 instances each and each
class refers to a type of iris plant. The dataset has two features: sepal length, sepal width. The third
column is for species, which holds the value for these types of plants. A new plant is identified. You
have to classify the Species class of new identified plant with the help of KNN algorithm.
Sepal Length
Sepal Width
Species
5.3
3.7
Setosa
5.1
3.8
Setosa
7.2
3.0
Virginica
5.4
3.4
Setosa
5.1
3.3
Setosa
5.4
3.9
Setosa
7.4
2.8
Virginica
6.1
2.8
Verscicolor
7.3
2.9
Virginica
6.0
2.7
Verscicolor
5.8
2.8
Virginica
6.3
2.3
Verscicolor
5.1
2.5
Verscicolor
6.3
2.5
Verscicolor
5.5
2.4
Verscicolor
Sepal Length
5.2
Sepal Width
3.1
Species
Transcribed Image Text:Consider the below given iris data set. This dataset contains 3 classes of 15 instances each and each class refers to a type of iris plant. The dataset has two features: sepal length, sepal width. The third column is for species, which holds the value for these types of plants. A new plant is identified. You have to classify the Species class of new identified plant with the help of KNN algorithm. Sepal Length Sepal Width Species 5.3 3.7 Setosa 5.1 3.8 Setosa 7.2 3.0 Virginica 5.4 3.4 Setosa 5.1 3.3 Setosa 5.4 3.9 Setosa 7.4 2.8 Virginica 6.1 2.8 Verscicolor 7.3 2.9 Virginica 6.0 2.7 Verscicolor 5.8 2.8 Virginica 6.3 2.3 Verscicolor 5.1 2.5 Verscicolor 6.3 2.5 Verscicolor 5.5 2.4 Verscicolor Sepal Length 5.2 Sepal Width 3.1 Species
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