(25) How would you explain Hidden Markov to a 12-year-old? - Quora

Markov Chain:
Say, some kids are spending a day at an amusement park. They have no set plans, they just wander from place to place. There's a chance they may go to the Towers, there's a chance they may go to the train ride. At any given point, it's hard to say where they might go next.

But the next destination is not completely random. Since teleporting has not yet been invented, they cannot suddenly jump from one side of the park to the other. So they'll go from one place to somewhere that's next to it. It depends on how far the walk is and what looks interesting.

If you draw a trace linking all the places they go to through the day, it would look like a 'chain of events'. Now imagine another group of kids wandering through the park, the sequence of where they go could be quite different. If you look at another group, it would be different again. But everyone of these would look like a chain. Mathematicians call these "Markov chains".

The same works with a zoo:

Hidden Markov
Now imagine, as the group of kids are wandering through the zoo, one of them phones a friend, and says: "I'm at the zoo! Let's play I Spy!"

Now imagine you are playing this game on the other end of the phone, trying to guess one animal after another, as the other kid wanders through the zoo. Since it's over the phone, you cannot see and don't always know where he is. That's why it's a "hidden" game.

Sometimes you get it right, "Yes, it an owl!" And it helps you with the next game.

You would think:

"Hmmm, it's probably still at the place where birds live. So this animal is also a bird."

Or,

"I know the elephant are not far from where the giraffes are..."

You are doing two things here. First you are using the cues to guess what the animal is; then, you are also using what you already know and guesses about which part of the zoo it is as hints to help you guess the animal.

The more hints you have, the easier it is to figure out exactly where your friend is and exactly what animal he or she is looking at.

And that's what Hidden Markov is about: figuring out something you can't always see from the bits and pieces that you can see or that you already know.

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