Question

A multivariate logistic regression model has been built to predict the propensity of

shoppers to perform a repeat purchase of a free gift that they are given. The

descriptive features used by the model are the age of the customer, the

socio-economic band to which the customer belongs (a, b, or c), the average amount

of money the customer spends on each visit to the shop, and the average number of

visits the customer makes to the shop per week. This model is being used by the

marketing department to determine who should be given the free gift. The weights in

the trained model are shown in the table below:

Feature Weight

Intercept -3.82398

Age -0.02990

Socio Economic Band B -0.09089

Socio Economic Band C -0.19558

Shop Value 0.02999

Shop Frequency 0.74572

Using this model to make predication for each of the following query instances:

ID Age Socio Economic Band Shop Frequency Shop Value

1 56 B 1.60 109.32

2 21 C 4.92 11.28

3 48 B 1.21 161.19

4 37 C    0.72 170.65

5   32 A 1.08 165.39

Answer 1

PLEASE GIVE IT A THUMBS UP, I SERIOUSLY NEED ONE, IF YOU NEED ANY MODIFICATION THEN LET ME KNOW, I WILL DO IT FOR YOU

while entering information in regression equation when it is band B , multiply brand B coefficient by 1 and brand C coefficient by 0. For brand A, both coefficients of brand B and C would be multiplied by 0.