January 2018
Beginner to intermediate
316 pages
7h 14m
English
Oftentimes, we hear about feature engineering in the specific context of supervised learning, otherwise known as predictive analytics. Supervised learning algorithms specifically deal with the task of predicting a value, usually one of the attributes of the data, using the other attributes of the data. Take, for example, the dataset representing the network intrusion:
|
DateTime |
Protocol |
Urgent |
Malicious |
|
June 2nd, 2018 |
TCP |
FALSE |
TRUE |
|
June 2nd, 2018 |
HTTP |
TRUE |
TRUE |
|
June 2nd, 2018 |
HTTP |
TRUE |
FALSE |
|
June 3rd, 2018 |
HTTP |
FALSE |
TRUE |
This is the same dataset as before, but let's dissect it further in the context of predictive analytics.
Notice that we have four attributes of ...
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