Fraud detection system using machine learning

our chosen project subject is ” FRAUD DETECTION SYSTEM USING
MACHINE LEARNING “

write a brief proposal (at most one-page, 12-point font, single spacing, 1 inch margins) that describes the idea for a project, the work you intend to perform, and all the people involved in the project (4 people). In particular, it should identify the project type, the problem you plan to address, the motivation for why you find the problem important or interesting, any previous work you already know about, and a rough tentative approach to solving the problem (if applicable) .

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In the group project, each group (three to four students) will focus on a topic and comes with a research/technical paper by the end of the semester. The topic should be on any specific security topic, but the expectation is to define a specific problem for in-depth investigation, coming up with a new solution (conceptual or practical application) and compare with similar other approaches extensively.

Your research project paper must include at least 15 articles from IEEE or ACM digital library and should follow IEEE format.

A good resource to search for journal and conference papers: https://scholar.google.com/

There are various types of projects you can consider:

The project may be very practical in terms of applying techniques you have learned in the course to a real problem such as classification of email messages
The project may involve designing or adapting existing algorithms to a novel class of problems. For example, how might we solve multiple related classification tasks? How can we improve document clustering by designing a new clustering metric?
The project may consist of a theoretical analysis of a method we have discussed. For example, this may be in terms of complexity, convergence, etc.
The project can be a theoretical or more applied survey of a branch of machine learning that we didn’t go through in detail. For example, you may write about the use of machine learning in different domains.

The requirement of the research project is to conduct machine learning techniques using a Weka package or other available programs. You can use any packages or any programming language.

Data can be collected from public domains or from your company.

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July 1, 2023

5) What criteria are available in determining which of two alternate cost function estimates is better for a particular management decision?

A) goodness of fit

B) economic plausibility

C) the significance of the difference between the costs associated with the highest and lowest observations of the cost driver

D) the significance of the difference between the unit values for the highest and lowest observations of the cost driver

E) the goodness of fit and economic plausibility

6) Which of the following is/are one of the criteria used when a manager evaluates an estimated cost function for decision making purposes?

A) economic plausibility

B) goodness of fit

C) irrelevant high-low outliers

D) specifications analysis

E) economic plausibility and goodness of fit

7) In multiple regression, when two or more independent variables are correlated with one another, the situation is known as

A) heteroscedasticity.

B) homoscedasticity.

C) spurious correlation.

D) autocorrelation.

E) multicollinearity.

8) Multicollinearity exists when which of the following conditions is present?

A) At least two variables change due to changes in the cost driver.

B) There are at least two cost pools (usually separated for fixed and variable costs).

C) The underlying value of the coefficient can only be explained in relation to dependent variables.

D) There are two or more statistically significant observations of at least two independent variables.

E) Two or more independent variables are highly correlated with each other.

9) In regression analysis, the term independence of residuals means

A) the residual term for any one observation is not related to the residual term of any other observation.

B) the data exhibit serial correlation.

C) the data exhibit autocorrelation.

D) there is a systematic pattern of positive residuals.

E) there is a systematic pattern of either only positive or only negative residuals.

10) Larson's Stables uses two different independent variables in two different equations to evaluate the cost activities of training horses, trainer's hours, and number of horses. The most recent year's results of the two regressions are as follows:

Trainer's hours:

Variable

Coefficient

Standard Error

t-Value

Constant

913.32

198.12

4.61

Predictor Variable

20.90

2.94

7.11

r2 = 0.56

Number of horses:

Variable

Coefficient

Standard Error

t-Value

Constant

4,764.50

1,073.09

4.44

Predictor Variable

864.98

247.14

3.50

r2 = 0.63

What is the estimated cost for the coming year if 16,000 trainer hours are incurred and the stable has 400 horses to be trained based on the best cost driver?

A) $33,555.50

B) $99,929.09

C) $350,756.50

D) $335,313.32

E) $13,844,444.50

11) C. M. Chain was to manufacture 1,000 chain saws next month. Its accountant has provided the following analysis of the total manufacturing costs.

Variable

Coefficient

Standard Error

t-Value

Constant

200

143.88

1.39

Predictor Variable

400

183.49

2.18

r2 = 0.71

What is the estimated cost of producing the 1,000 chain saws?

A) $400,200

B) $284,142

C) $200,400

D) $18,000

E) $9,000

12) Goodness-of-fit measures how well the predicted values in a cost estimating equation

A) match the cost driver.

B) match the actual cost observations.

C) fit the coefficient of determination.

D) rely on the independent variable.

E) rely on the dependent variable

13) Which of the following statements about a high correlation between two variables s and t is FALSE?

A) s may cause t.

B) t may cause s.

C) They both may be affected by a third variable.

D) The correlation establishes an economically plausible relationship between costs and their cost drivers.

E) The correlation may be due to random chance.

Use the information below to answer the following question(s).

Bernie Company used regression analysis to predict the annual cost of indirect materials. The results were as follows:

Indirect Materials Cost Explained by Units Produced

Constant

$4,378

Standard error of Y estimate

$912

R - squared

0.9183

No. of observations

Degrees of freedom

X coefficient

2.35

Standard error of coefficient(s)

0.437525

14) The linear cost function is

A) Y =.$918 + 0.44X.

B) Y = $912 + $1.03X.

C) Y = $4,020 + $0.92X.

D) Y = $4,378+ $0.92X.

E) Y = $4,378 + $2.35X.