January 2019
Intermediate to advanced
294 pages
6h 43m
English
Content preview from Machine Learning Quick Reference
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How the Naive Bayes classifier works
We will try to understand all of this by looking at the example of the Titanic. While the Titanic was sinking, a few of the categories had priority over others, in terms of being saved. We have the following dataset (it is a Kaggle dataset):
|
Person category |
Survival chance |
|
Woman |
Yes |
|
Kid |
Yes |
|
Kid |
Yes |
|
Man |
No |
|
Woman |
Yes |
|
Woman |
Yes |
|
Man |
No |
|
Man |
Yes |
|
Kid |
Yes |
|
Woman |
No |
|
Kid |
No |
|
Woman |
No |
|
Man |
Yes |
|
Man |
No |
|
Woman |
Yes |
Now, let's prepare a likelihood table for the preceding information:
|
|
|
Survival chance |
|
|
|
|
|
|
No |
Yes |
Grand Total |
|
|
|
|
Category |
Kid |
1 |
3 |
4 |
4/15= |
0.27 |
|
Man |
3 |
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