Loading...

Messages

Proposals

Stuck in your homework and missing deadline? Get urgent help in $10/Page with 24 hours deadline

Get Urgent Writing Help In Your Essays, Assignments, Homeworks, Dissertation, Thesis Or Coursework & Achieve A+ Grades.

Privacy Guaranteed - 100% Plagiarism Free Writing - Free Turnitin Report - Professional And Experienced Writers - 24/7 Online Support

Naive bayes on iris dataset in r

27/11/2021 Client: muhammad11 Deadline: 2 Day

School of Computer & Information Sciences

ITS 836 Data Science and Big Data Analytics

ITS 836

1

HW07 Lecture 07 Classification

Questions

Perform the ID3 Algorithm

R exercise for Decision Tree section 7_1

Explain how Random Forest Algorithm works

Iris Dataset with Decision Tree vs Random Forest

R exercise for Naïve Bayes section 7_2

Analyze Classifier Performance section 7_3

Redo calculations for ID3 and Naïve Bayes for the Golf

ITS 836

2

HW07-1 Apply ID3 Algorithm to demonstrate the Decision Tree for the data set

ITS 836

3

http://www.cse.unsw.edu.au/~billw/cs9414/notes/ml/06prop/id3/id3.html

Select Size Color Shape
yes medium blue brick
yes small red sphere
yes large green pillar
yes large green sphere
no small red wedge
no large red wedge
no large red pillar
Back to HW07 Overview

HW07 Q 2

Analyze R code in section 7_1 to create the decision tree classifier for the dataset: bank_sample.csv

Create and Explain all plots an d results

ITS 836

4

# install packages rpart,rpart.plot

# put this code into Rstudio source and execute lines via Ctrl/Enter

library("rpart")

library("rpart.plot")

setwd("c:/data/rstudiofiles/")

banktrain <- read.table("bank-sample.csv",header=TRUE,sep=",")

## drop a few columns to simplify the tree

drops<-c("age", "balance", "day", "campaign", "pdays", "previous", "month")

banktrain <- banktrain [,!(names(banktrain) %in% drops)]

summary(banktrain)

# Make a simple decision tree by only keeping the categorical variables

fit <- rpart(subscribed ~ job + marital + education + default + housing + loan + contact + poutcome,method="class",data=banktrain,control=rpart.control(minsplit=1),

parms=list(split='information'))

summary(fit)

# Plot the tree

rpart.plot(fit, type=4, extra=2, clip.right.labs=FALSE, varlen=0, faclen=3)

Back to HW07 Overview

4

HW07 Q 2

Analyze R code in section 7_1 to create the decision tree classifier for the dataset: bank_sample.csv

Create and Explain all plots an d results

ITS 836

5

5

HW07 Q 2

Analyze R code in section 7_1 to create the decision tree classifier for the dataset: bank_sample.csv

Create and Explain all plots and results

ITS 836

6

6

HW 7 Q3

Explain how a Random Forest Algorithm Works

ITS 836

7

http://blog.citizennet.com/blog/2012/11/10/random-forests-ensembles-and-performance-metrics

Back to HW07 Overview

ITS 836

Use Decision Tree Classifier and Random Forest

Attributes: sepal length, sepal width, petal length, petal width

All flowers contain a sepal and a petal

For the iris flowers three categories (Versicolor, Setosa, Virginica) different measurements

R.A. Fisher, 1936

8

HW07 Q4 Using Iris Dataset

Back to HW07 Overview

HW07 Q4 Using Iris Dataset

Decision Tree applied to Iris Dataset

https://rpubs.com/abhaypadda/k-nn-decision-tree-on-IRIS-dataset or

https://davetang.org/muse/2013/03/12/building-a-classification-tree-in-r/

What are the disadvantages of Decision Trees?

https://www.quora.com/What-are-the-disadvantages-of-using-a-decision-tree-for-classification

Random Forest applied to Iris Dataset and compare to

https://rpubs.com/rpadebet/269829

http://rischanlab.github.io/RandomForest.html

ITS 836

9

Get data and e1071 package

sample<-read.table("sample1.csv",header=TRUE,sep=",")

traindata<-as.data.frame(sample[1:14,])

testdata<-as.data.frame(sample[15,])

traindata #lists train data

testdata #lists test data, no Enrolls variable

install.packages("e1071", dep = TRUE)

library(e1071) #contains naïve Bayes function

model<-naiveBayes(Enrolls~Age+Income+JobSatisfaction+Desire,traindata)

model # generates model output

results<-predict(model,testdata)

Results # provides test prediction

ITS 836

10

Q5 HW07 Section 7.2 Naïve Bayes in R

Back to HW07 Overview

10

7.3 classifier performance

# install some packages

install.packages("ROCR")

library(ROCR)

# training set

banktrain <- read.table("bank-sample.csv",header=TRUE,sep=",")

# drop a few columns

drops <- c("balance", "day", "campaign", "pdays", "previous", "month")

banktrain <- banktrain [,!(names(banktrain) %in% drops)]

# testing set

banktest <- read.table("bank-sample-test.csv",header=TRUE,sep=",")

banktest <- banktest [,!(names(banktest) %in% drops)]

# build the na?ve Bayes classifier

nb_model <- naiveBayes(subscribed~.,

data=banktrain)

ITS 836

11

# perform on the testing set

nb_prediction <- predict(nb_model,

# remove column "subscribed"

banktest[,-ncol(banktest)],

type='raw')

score <- nb_prediction[, c("yes")]

actual_class <- banktest$subscribed == 'yes'

pred <- prediction(score, actual_class)

perf <- performance(pred, "tpr", "fpr")

plot(perf, lwd=2, xlab="False Positive Rate (FPR)",

ylab="True Positive Rate (TPR)")

abline(a=0, b=1, col="gray50", lty=3)

## corresponding AUC score

auc <- performance(pred, "auc")

auc <- unlist(slot(auc, "y.values"))

auc

Back to HW07 Overview

7.3 Diagnostics of Classifiers

We cover three classifiers

Logistic regression, decision trees, naïve Bayes

Tools to evaluate classifier performance

Confusion matrix

ITS 836

12

Back to HW07 Overview

12

7.3 Diagnostics of Classifiers

Bank marketing example

Training set of 2000 records

Test set of 100 records, evaluated below

ITS 836

13

Back to HW07 Overview

13

HW07 Q07 Review calculations for the ID3 and Naïve Bayes Algorithm

ITS 836

14

Record OUTLOOK TEMPERATURE HUMIDITY WINDY PLAY GOLF
X0 Rainy Hot High False No
X1 Rainy Hot High True No
X2 Overcast Hot High False Yes
X3 Sunny Mild High False Yes
4 Sunny Cool Normal False Yes
5 Sunny Cool Normal True No
6 Overcast Cool Normal True Yes
7 Rainy Mild High False No
8 Rainy Cool Normal False Yes
9 Sunny Mild Normal False Yes
10 Rainy Mild Normal True Yes
11 Overcast Mild High True Yes
12 Overcast Hot Normal False Yes
X13 Sunny Mild High True No
Back to HW07 Overview

Questions?

ITS 836

15

Homework is Completed By:

Writer Writer Name Amount Client Comments & Rating
Instant Homework Helper

ONLINE

Instant Homework Helper

$36

She helped me in last minute in a very reasonable price. She is a lifesaver, I got A+ grade in my homework, I will surely hire her again for my next assignments, Thumbs Up!

Order & Get This Solution Within 3 Hours in $25/Page

Custom Original Solution And Get A+ Grades

  • 100% Plagiarism Free
  • Proper APA/MLA/Harvard Referencing
  • Delivery in 3 Hours After Placing Order
  • Free Turnitin Report
  • Unlimited Revisions
  • Privacy Guaranteed

Order & Get This Solution Within 6 Hours in $20/Page

Custom Original Solution And Get A+ Grades

  • 100% Plagiarism Free
  • Proper APA/MLA/Harvard Referencing
  • Delivery in 6 Hours After Placing Order
  • Free Turnitin Report
  • Unlimited Revisions
  • Privacy Guaranteed

Order & Get This Solution Within 12 Hours in $15/Page

Custom Original Solution And Get A+ Grades

  • 100% Plagiarism Free
  • Proper APA/MLA/Harvard Referencing
  • Delivery in 12 Hours After Placing Order
  • Free Turnitin Report
  • Unlimited Revisions
  • Privacy Guaranteed

6 writers have sent their proposals to do this homework:

Quality Homework Helper
Essay Writing Help
Assignment Solver
Coursework Helper
Engineering Solutions
Custom Coursework Service
Writer Writer Name Offer Chat
Quality Homework Helper

ONLINE

Quality Homework Helper

I am an experienced researcher here with master education. After reading your posting, I feel, you need an expert research writer to complete your project.Thank You

$41 Chat With Writer
Essay Writing Help

ONLINE

Essay Writing Help

I am a PhD writer with 10 years of experience. I will be delivering high-quality, plagiarism-free work to you in the minimum amount of time. Waiting for your message.

$15 Chat With Writer
Assignment Solver

ONLINE

Assignment Solver

I am an elite class writer with more than 6 years of experience as an academic writer. I will provide you the 100 percent original and plagiarism-free content.

$15 Chat With Writer
Coursework Helper

ONLINE

Coursework Helper

Being a Ph.D. in the Business field, I have been doing academic writing for the past 7 years and have a good command over writing research papers, essay, dissertations and all kinds of academic writing and proofreading.

$15 Chat With Writer
Engineering Solutions

ONLINE

Engineering Solutions

I will provide you with the well organized and well research papers from different primary and secondary sources will write the content that will support your points.

$28 Chat With Writer
Custom Coursework Service

ONLINE

Custom Coursework Service

After reading your project details, I feel myself as the best option for you to fulfill this project with 100 percent perfection.

$25 Chat With Writer

Let our expert academic writers to help you in achieving a+ grades in your homework, assignment, quiz or exam.

Similar Homework Questions

DP Short Answer 2 - Business math and statistical measures - Africa in world history gilbert 3rd edition chapter summaries - Research paper - Psychotherapy a Biological Basis - Personal shopper topshop salary - Toyota starlet dashboard lights - Assessment 2 - The ways we lie analysis - Fran cubberley - A long way home - Argumentative essay on phones in school - Aerospace dynamics will invest $110 000 - Psalm 119 105 kjv - Australian catholic social justice - Lesson 9 Scientific Notation in the Real World - How to find pkb from kb - Derbyshire county council blue badge - Deconstructing an advertisement assignment - Differentiator with product lifecycle focus - Csa class 1 div 2 - Vegetarianism - What are persuasive techniques - Chemistry lab report rubric - The element of self-concept that we dream of or dread are called our - St davids practice stanwell - Genogram narrative - How are tv shows written in an essay - A 1500 kg car skids to a halt on a wet road where μk = 0.53. - One Page Argumentative Essay - Paper - Mary seacole building salford - Waste management accounting scandal wikipedia - How do you factorise cubics - A company that handles hazardous waste wants to minimize - Sam richards a radical experiment in empathy - The crucible online book act 2 - Describe the treatment of women at the humanist schools - Barbano v madison county case brief - Six steps to ethical decision making - Starsound orchestra here comes the bride - Field hockey attacking tactics - 300 words not including references - Oxidation reduction reactions lab answers - Parallel operation of alternators sample problems - Converging and diverging lenses - How does high humidity affect aircraft performance - Early followers of jesus who spread his message - Map of zambia with towns - Eba definition of forbearance - The mask we live in documentary - Notes - SBAR - Concordia university registrar office - Jane eyre discussion questions - Role of theory in research - Ben stacy blue man - Leaf rubbing lesson plan - Article review - Sunpower e20 327 e ac - Microeconomics - W9 law - Cambridge teacher knowledge test - Relative reactivity of metals - Three grams of musk oil are required for each - Mary fisher speech analysis - Nasm workout template - Digital scale calibration instructions - Data Visualization Project Plan - Ethical issues raised by the milgram study - What is back titration pdf - Eco log maker review - Our father in chinese - Nurses as knowledge workers definition - Bupa change of details form - Pi controller block diagram - Taylormade r540 xd driver illegal - Parkinson v college of ambulance - Discussion - Skeptics and the art of persuasion os guiness audio - Richard taylor three characteristics for a meaningful life - What is the epic hero cycle - Absolute wbc count formula - Work - Taxonomy life's filing system crash course biology video answer key - Board of intermediate and secondary education peshawar - Is macconkey agar chemically defined - Hanging scaffolding method statement - An operations strategy for inventory management should work toward - Design an algorithm - Bloomberg businessweek b school connection program - Fairness and equality in the classroom - Case study - Countable and uncountable sets in discrete mathematics - Map of sydney olympic park - Construction training institute helensvale - Hartz frisky frolic ice cream cone - Ass 7 - Difference between word addressable and byte addressable - Co2 covalent compound name