urve, you can guess, 2 or 3 different numbers of clusters, depending on how the elbow bends ( the sharper the elbow bends, meaning the error drops very sharpy, then pick 1 k, if the error drops NOT so sharply, then pick 2, 3, or 4 different k
urve, you can guess, 2 or 3 different numbers of clusters, depending on how the elbow bends ( the sharper the elbow bends, meaning the error drops very sharpy, then pick 1 k, if the error drops NOT so sharply, then pick 2, 3, or 4 different k
Chapter5: Working With Excel Tables, Pivottables, And Pivotcharts
Section: Chapter Questions
Problem 11RA
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Question
Given:
Ggplot2 and K-means Method in R
install.packages("ggplot2")library(ggplot2)# load the datesetdata(mtcars)
after drawing the elbow curve, you can guess, 2 or 3 different numbers of clusters, depending on how the elbow bends ( the sharper the elbow bends, meaning the error drops very sharpy, then pick 1 k, if the error drops NOT so sharply, then pick 2, 3, or 4 different k value.
Sharpy e.g 90 degree bend not so sharply e.g 45 - 60 degree
you MUST summarize your results, e.g. your choice(s) of number of clusters, relationship between wt and mpg etc.
any relationship between mpg and wt?
![You must do the following
data (mtcars) # load the dateset
# use only three colunms,
ds <- mtcarsL, c("mpg", "cxl", "wt")]
# convert the cyl into factor (labels)
dsscyl <- as factor(dsicyl)
Use K-means to cluster the dataset “ds" we have used in previous lesson, then plot the points, the
clusters, and the centers together with different colors. First, use the "elbow" method to find the
number of clusters, K. Finally, summarize the results. Put your code, plots, and summary in a word
file, upload this word file to SOUL.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F5aa8e2c7-43e7-4c99-9185-2f4cea0d8634%2F7d1f0c21-483d-42dc-89f7-1f86c3abd134%2F8wdyogo_processed.png&w=3840&q=75)
Transcribed Image Text:You must do the following
data (mtcars) # load the dateset
# use only three colunms,
ds <- mtcarsL, c("mpg", "cxl", "wt")]
# convert the cyl into factor (labels)
dsscyl <- as factor(dsicyl)
Use K-means to cluster the dataset “ds" we have used in previous lesson, then plot the points, the
clusters, and the centers together with different colors. First, use the "elbow" method to find the
number of clusters, K. Finally, summarize the results. Put your code, plots, and summary in a word
file, upload this word file to SOUL.
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