Will give brainliest

A data mining routine has been applied to a transaction dataset and has classified 88 records as fraudulent (30 correctly so) an

Firlakuza [10]

Answer:

The classification matrix is attached below

Part a

The classification error rate for the records those are truly fraudulent is 65.91%.

Part b

The classification error rate for records that are truly non-fraudulent is 96.64%

Step-by-step explanation:

The classification matrix is obtained as shown below:

The transaction dataset has 30 fraudulent correctly classified records out of 88 records, that is, 30 records are correctly predicted given that an instance is negative.

Also, there would be 88 - 30 = 58 non-fraudulent incorrectly classified records, that is, 58 records are incorrectly predicted given that an instance is positive.

The transaction dataset has 920 non-fraudulent correctly classified records out of 952 records, that is, 920 records are correctly predicted given that an instance is positive.

Also, there would be 952 - 920 = 32 fraudulent incorrectly classified records, that is, 32 records incorrectly predicted given that an instance is negative.

That is,

Predicted value

Active value Fraudulent Non-fraudulent

Fraudlent 30 58

non-fraudulent 32 920

The classification matrix is obtained by using the information related to the transaction data, which is classified into fraudulent records and non-fraudulent records.

The error rate is obtained as shown below:

The error rate is obtained by taking the ratio of $\left( {b + c} \right)(b+c)$ and the total number of records.

The classification matrix is, shown above

The total number of records is, $30 + 58 + 32 + 920 = 1,040$

The error rate is,

$\begin{array}{c}\\{\rm{Error}}\,{\rm{rate}} = \frac{{b + c}}{{{\rm{Total}}}}\\\\ = \frac{{58 + 32}}{{1,040}}\\\\ = \frac{{90}}{{1,040}}\\\\ = 0.0865\\\end{array}$

The percentage is $0.0865 \times 100 = 8.65$

(a)

The classification error rate for the records those are truly fraudulent is obtained by taking the rate ratio of b and $\left( {a + b} \right)(a+b)$ .

The classification error rate for the records those are truly fraudulent is obtained as shown below:

The classification matrix is, shown above and in the attachment

The error rate for truly fraudulent is,

$\begin{array}{c}\\FP = \frac{b}{{a + b}}\\\\ = \frac{{58}}{{30 + 58}}\\\\ = \frac{{58}}{{88}}\\\\ = 0.6591\\\end{array}$

The percentage is, $0.6591 \times 100 = 65.91$

(b)

The classification error rate for records that are truly non-fraudulent is obtained by taking the ratio of d and $\left( {c + d} \right)(c+d)$ .

The classification error rate for records that are truly non-fraudulent is obtained as shown below:

The classification matrix is, shown in the attachment

The error rate for truly non-fraudulent is,

$\begin{array}{c}\\TP = \frac{d}{{c + d}}\\\\ = \frac{{920}}{{32 + 920}}\\\\ = \frac{{920}}{{952}}\\\\ = 0.9664\\\end{array}$

The percentage is, $0.9664 \times 100 = 96.64$

6 0

3 years ago

Out of 600 seniors at a local high school, 60% went on the senior trip. At the hotel, one room was reserved for every 4 students

butalik [34]

Given:

Total number of senior students = 600

60% went on the senior trip.

One room was reserved for every 4 students.

To find:

The total number of reserved rooms.

Solution:

60% went on the senior trip from total 600 students. So, number of students who went on tripe is

$600\times \dfrac{60}{100}=360$

Now, one room was reserved for every 4 students. So,

$\text{Required number of rooms}=\dfrac{\text{Number of students who went on tripe}}{\text{Number of students in room}}$

$\text{Required number of rooms}=\dfrac{360}{4}$

$\text{Required number of rooms}=90$

Therefore, the required number of reserved rooms were 90.

4 0

3 years ago

How to solve for X 'Triangles sum Theorem'

guajiro [1.7K]

I guess this will be good example of how to do it

8 0

3 years ago

The barbers profit p each week depends on his charge c per haircut. It is modeled by the equation p= -200c^2+2400c-4700. What pr

shepuryov [24]

Answer:

0 ≤ c ≤ 12

Step-by-step explanation:

The function can be rearranged to ...

p = 200c(12 -c) -4700

suggesting that revenue will be zero for a charge of 0 or for a charge of 12, and that fixed expenses are 4700. Charges less than 0 are uninteresting, and charges high enough to cause the number of customers to be negative also don't make any sense in this context.

Though out of the range of likely consideration, charges low or high enough to cause profit to be negative (more than 9.54, for example) seemingly can be reasonably modeled by this function.

5 0

3 years ago

Anyone need help with math i not that good with word problems but i could help

Setler79 [48]

sure. or u could google them...

7 0

4 years ago