Update README.md

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André Almeida 2019-05-09 07:48:54 -07:00
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This repository have two different exercises in erlang:
1. Decision tree that maximizes the optimal point and consequently provides decision support based on the assumptions provided.
**1. **Decision tree that maximizes the optimal point and consequently provides decision support based on the assumptions provided.
* The probability of making a medication/treatment 1 and use is OK of 42%;
* One possibility of making a medication/treatment 1 and of the user staying KO is 22.5%;
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![alt text](https://i.postimg.cc/5207cpvs/Captura-de-ecr-2019-04-09-s-13-06-01.png)
2. There are ways to get the probabilities knowing certain parameters (they do not indicate the optimal point, but calculate a probability of success depending on the existing resources) - using the baysian networks.
**2. **There are ways to get the probabilities knowing certain parameters (they do not indicate the optimal point, but calculate a probability of success depending on the existing resources) - using the baysian networks.
What is the probability of giving the patient M2 and is OK, knowing that: