Week Six 16 (1).pdf

Artificial Intelligence Intelligence Wester Zela Week Six [email protected] www.ssyspe.org

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Bayesian Bayesian Network

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Examples: Cervical Spondylotic Myelophaty (CSM)

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Test

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Bayesian Bayesian Network in Weka









Bayesian Network •

It can be referred referred as probabilistic directed di rected acyclic graphical (DAG) (DAG) model, Bayes Network, Belief Network, or Bayesian Model.

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Based on a set of variables connected, it’ it ’s possible to predict outcomes based on probabilities. The resulting value of one variable will influence the output probability of another, hence the use of









A little graph theory •

Nodes and edges are connected.









A Little probability theory •

Coin Flip: • • •

P(Coin toss will be heads) heads) = 0.5 (50%) P(Coin toss will be tails)=0.5 (50%) What is the probability of two heads? p(heads)x P(heads)=0.5x0.5=0.25 or p(Heads first time | Heads second s econd time)









Bayes Theorem •

The important part of Bayes’ Bayes’ Theorem is the observation of previous events, or your degree d egree of belief that something will wi ll occur. occur.

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If you have a degree of belief of one event happening, you can apply it to new data and make an informed calculation to its probability. probability.











Bayes Theorem









An example:









Assigning Probabilities Probabilities









Calculating Results









Calculating results





























































Classifier Bayes Net.K2









Setting parameters •

initAsNaiveBayes: Cuando se establece en True será una red con una flecha desde el nodo de clasificador a cada nodo. Cuando se establece en falso, la estructura inicial corresponderá a una red vacía.

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markovBlanketClassier: Cuando se establece en true se asegura que todos los nodos de la red forman parte de la manta de Markov









Setting parameters •

randomOrder: Cuando se establece en true, el orden de los nodos de la red es al azar. El valor predeterminado es false y se utiliza el orden que traen los nodos en el conjunto de datos.

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scoreType: El tipo de puntuación determina la medida utilizada para evaluar la calidad de una estructura de red.









R Studio •

Install R • •

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https://cran.r-project.org/mirrors.html https://www.rstudio.com/products/rstudio/download/

Install the bnlearn package http://www.bnlearn.com/examples/









Ranking in ssyspe.org: ssyspe.org: 28/04 •

PTOi = 2NPi + 0.5NPA i user_id Score 28/04 Ptos 28/04 1580

12.5

3

1565

12

3

1368

9

2

1563

4.5

1











Paper of Week









References

Week Six 16 (1).pdf

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