Email Classification Using Data Reduction Method
Rafiqul Islam and Yang Xiang, member IEEE
School of Information Technology
Deakin University, Burwood 3125, Victoria, Australia
Abstract Classifying user emails correctly from penetration of
spam is an impo
1
Short Paper
Short Paper: Effects of Cybercrime on State Security Types, Impact and
Mitigations with the Fiber Optic Deployment in Kenya
DMGT 830
March 26, 2013
2
Short Paper 2-
Introduction
Cybercrime is a growing problem for the globalized world due to
Statistics Definitions
T-test can be used to test whether there is a difference between the means of some variable
It is the type of variable(s) involved that determines the appropriate test to employ, that is, t-test
or chi-square or some other statistic
When you determine if there is an association between two variables, it is also important for
you to determine how strong or weak that association is. This is why, when you have data
for two quantitative variables, you calculate what is called the coeffic
Chi-square Contingency Table Test for Independence
Male
Female
Total
CollegeNot
Graduate
a College Graduate
Total
Observed
56
32
88
Expected
54.37
33.63
88.00
O-E
1.63
-1.63
0.00
(O - E) / E
0.05
0.08
0.13
Observed
62
41
103
Expected
63.63
39.37
103.00
O-
You have seen that you could calculate what is called the correlation
coefficient when you have data for two quantitative variables to see if those
variables might have a linear relationship. If the variables do have a linear
relationship, the next step i
For this assignment, you will view a video about the steps of a new kind of hypothesis test
called the Chi Square Test of Independence. After watching the video, you will answer questions
in which you determine if there is an association between two categ
http:/ncalculators.com/math-worksheets/coefficient-variationexample.htm
Coefficient of variation (CV)
Definition:
Coefficient of Variation is the percentage variation in mean,
standard deviation being considered as the total variation in the
mean. If we w
Desmos Graphing Calculator and Linear Regression
You can use the free online Desmos Graphing Calculator to produce a scatterplot and find the regression line and correlation coefficient.
Go to https:/www.desmos.com/calculator and lau
unch the calculator.
http:/www.investopedia.com/ask/answers/032515/what-does-itmean-if-correlation-coefficient-positive-negative-or-zero.asp
What does it mean if the correlation coefficient is positive,
negative, or zero?
Correlation Coefficient
Thecorrelationcoefficientmeasu
Confounding variable - Correlation vs Causation
An interesting concept that was introduced to me through the studies on birth order is the concept
of the confounding variable. A confounding variable is an extraneous variable in a statistical
model that co
October 2016
Budget
Income
Expenses
Full time
$4,500.00 Rent
Part time
$850.00 Food
Car
Gas
Other
$400.00 Student Loan
Utilities
Total
Savings
$950.00 Goal
$150.00 Available
$200.00 Months
$20.00
$1,500.00
$300.00
$1,380.00 Essentials
$50.00
Insurance
$15
International Journal of Computer Science & Engineering Survey (IJCSES) Vol.3, No.4, August 2012
WEB SEARCH RESULT CLUSTERING- A REVIEW
Kishwar Sadaf1 and Mansaf Alam2
1
Department of Computer Science, Jamia MIllia Islamia, New Delhi, India
kishwarsadaf@g
4
Decision Tree Induction: Using Entropy
for Attribute Selection
4.1 Attribute Selection: An Experiment
In the last chapter it was shown that the TDIDT algorithm is guaranteed to
terminate and to give a decision tree that correctly corresponds to the data
Naive-Bayes Classification Algorithm
1. Introduction to Bayesian Classification
The Bayesian Classification represents a supervised learning method as well as a statistical
method for classification. Assumes an underlying probabilistic model and it allows
Neural Network Prediction Model
Inputs and outputs
Network ArchitectureOptions
Number of Inputs ( bewtween 2 and 50)
13
Number of Outputs ( between 1 and 10 )
Number of Hidden Layers ( 1 or 2 )
1
Hidden Layer sizes ( Maximum 20 )
Learning parameter (betwe
8
Avoiding Overtting of Decision Trees
The Top-Down Induction of Decision Trees (TDIDT) algorithm described in
previous chapters is one of the most commonly used methods of classication. It is well known, widely cited in the research literature and an imp
Rafal Ladysz: FINAL PROJECT PAPER
for INFS 795, Fall 2004 (Professor Carlotta Domeniconi)
CLUSTERING OF EVOLVING TIME SERIES DATA:
an attempt to optimize the number and initial positions of cluster centroids
for k-means clustering with regards to goodness
Consider the transformations listed at the top of page 38 in Chapter 2 and in
Chapter 8, pp 171-218 of the SPSS Base 15.0 Users Guide. Another link to the guide
is http:/bingweb.binghamton.edu/docs/spss/SPSS%20Base%20User's%20Guide
%2015.0.pdf More materi
In your study group, specify the target variable in your dataset, a variable to classify
or predict? Which of the other variables in your dataset could help identify the
target? Are there any methods in the choice of readings that could be used to
answer
Machine Learning with WEKA
WEKA Explorer Tutorial
for WEKA Version 3.4.3
Svetlana S. Aksenova
aksenovs@ecs.csus.edu
School of Engineering and Computer Science
Department of Computer Science
California State University, Sacramento
California, 95819
2004
TA
Statistics ANOVA
Background Dataset
Using the data in the table below answer the following questions.
1. Based on output from ANOVA, who is the better bowler? Show the step-by-step calculation of ANOVA.
2. What type of ANOVA test did you conduct? one way?