Unit 4, 7 Rejection SamplingYouTube↗  IA↗(long shot)
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But there's a problem with rejection sampling.
Mas há um problema com a amostragem por rejeição.
If the evidence is unlikely, you end up rejecting a lot of the samples.
Se a evidência é improvável, acabamos rejeitando um monte de amostras.
Let's go back to the alarm network where we had variables for burglary and for an alarm
Vamos voltar ao exemplo da rede do alarme, onde tínhamos variáveis para o roubo e para um alarme
and say when arrested, in computing the probability of a burglary,
digamos que estamos interessados em calcular a probabilidade do roubo,
given that the alarm goes off.
dado que o alarme disparou.
The problem is that burglaries are very infrequent,
O problema é que os roubos têm pouca frequência,
so most of the samples we would get would end up being--
então a maioria das amostras que conseguiríamos acabaria sendo--
we start with generating a B, and we get a -b and then a -a.
começamos gerando B, conseguimos um -b e depois um -a.
We go back and say does this match?
Voltamos e perguntamos se esse é o valor desejado.
No, we have to reject this sample,
Não, temos que rejeitar essa amostra,
so we generate another sample, and we get another -b, -a.
então geramos outra, e conseguimos outro -b, -a.
We reject that. We get another -b, -a.
Rejeitamos novamente. Pegamos outro -b, -a.
And we keep rejecting, and eventually we get a +b,
E aí continuamos rejeitando, até por ventura conseguirmos um +b,
but we'd end up spending a lot of time rejecting samples.
mas acabaremos perdendo muito tempo rejeitando amostras.
So, we're going to introduce a new method called likelihood weighting
Iremos introduzir um novo método chamado Reamostragem Ponderada,
that generates samples so that we can keep every one.
que gera amostras de forma que todas sejam mantidas.
With likelihood weighting, we fix the evidence variables.
Com reamostragem ponderada, podemos corrigir as variáveis de evidência.
That is, we say that A will always be positive,
Isto é, dizemos que A sempre será positivo,
and then we sample the rest of the variables,
e então fazemos a amostragem com o resto das variáveis,
so then we get samples that we want.
aí podemos obter as amostras que queremos.
We would get a list like -b, +a,
Obteríamos uma lista como -b, +a,
-b, +a,
-b, +a,
+b, +a.
+b, +a,
We get to keep every sample, but we have a problem.
Manteríamos todas as amostras, mas temos um problema.
The resulting set of samples is inconsistent.
O conjunto resultante de amostras é inconsistente.
We can fix that, however, by assigning a probability
Podemos corrigir isso, entretanto, atribuindo uma probabilidade
to each sample and weighing them correctly.
para cada amostra e ponderando corretamente.
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