EM-algorithm
Okay kiddo, have you heard of the EM algorithm? It's a way to help us figure out what kinds of things might be going on in a big pile of data that we don't know much about.
Here's how it works: first, we start with some guesses about what might be happening in the data. We call these guesses "parameters". We use these parameters to make some predictions about what the data should look like if our guesses are right.
Then, we look at the actual data and compare it to the predictions we made based on our guesses. We see what's different between the prediction and the actual data.
We take those differences and use them to update our guesses. We tweak our parameters so that our predictions are closer to the actual data.
We keep doing this over and over again, making new predictions, comparing them to the actual data, and updating our guesses. Each time we do this, our guesses get better and better, and our predictions get closer and closer to the actual data.
The EM algorithm is really helpful because sometimes we have a lot of data but we don't know much about it. This method helps us learn more about the data without having to look at every single piece of it. It helps us narrow down the possibilities so we can understand the data better.
Here's how it works: first, we start with some guesses about what might be happening in the data. We call these guesses "parameters". We use these parameters to make some predictions about what the data should look like if our guesses are right.
Then, we look at the actual data and compare it to the predictions we made based on our guesses. We see what's different between the prediction and the actual data.
We take those differences and use them to update our guesses. We tweak our parameters so that our predictions are closer to the actual data.
We keep doing this over and over again, making new predictions, comparing them to the actual data, and updating our guesses. Each time we do this, our guesses get better and better, and our predictions get closer and closer to the actual data.
The EM algorithm is really helpful because sometimes we have a lot of data but we don't know much about it. This method helps us learn more about the data without having to look at every single piece of it. It helps us narrow down the possibilities so we can understand the data better.