September 2016
Intermediate to advanced
316 pages
6h 43m
English
We need a good historical dataset to build our model. We will mine this dataset to build our model. To continue with the example to our fictitious company, Furnitica, we will use historical campaign response data from a previous campaign run by Furnitica.
This is synthetic data, which means it has been synthesized using a random data generation algorithm. A few sample rows in our dataset are presented in Table 2:
|
Age |
Income |
Gender |
Folder |
Response |
|
61 |
30974 |
0 |
1 |
0 |
|
42 |
38260 |
0 |
3 |
0 |
|
40 |
20135 |
0 |
4 |
0 |
|
88 |
30645 |
0 |
5 |
0 |
|
58 |
38078 |
1 |
3 |
0 |
|
73 |
20445 |
0 |
4 |
0 |
|
34 |
66198 |
0 |
3 |
0 |
|
65 |
48657 |
0 |
2 |
0 |
|
68 |
39309 |
0 |
1 |
0 |
Table 2 Sample credit card approval data
This dataset is generated from the response ...
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