I was working on a project which utilized the Markov chain. I had an interesting time solving a matrix manipulation problem. I thought I should share the problem here.
I am using Markov transition probabilities as a feature matrix for a machine learning algorithm but the problem is for a single document D it will create R rows for each state S R = D x S whereas the feature matrix should contain 1 R per D. So, the goal is to convert this R = D (1 row for 1 document)
Given the transition matrix of a Markov chain represented as a table in an SQL database. Each row in the table represents the probability of transitioning from one state to another. Please refer to Fig. 1 for a sample input format.
Each row represents the transition probabilities from a previous state (val) to a current state (a, b, c).
so it's important to note that a -> b is not equal to b -> a because the probability of change in the state of event a to state b would be different from the probability of change in the state of event b to a
Write a SQL query to generate all possible state combinations (e.g., a_a, a_b, a_c, b_a, b_b, b_c, c_a, c_b, c_c) along with their corresponding transition probabilities.
You are provided with a table named transition matrix having the following schema:
prev_state: Represents the previous state (can be a, b, or c).
a: Probability of transitioning to state a from the previous state.
b: Probability of transitioning to state b from the previous state.
c: Probability of transitioning to state c from the previous state.
The output should contain a single row representing all possible state combinations, where each state combination (e.g., a_a, a_b, a_c, b_a, b_b, b_c, c_a, c_b, c_c) serves as a column name. The corresponding cell values in this row should be the probabilities of transitioning between the states.
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Each state (a, b, c) can transition to any other state (a, b, c) based on the given probabilities.
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Probabilities are represented as decimal numbers between 0 and 1.
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Each state combination must appear as a column in the output even if the transition probability is 0.
You can use conditional aggregation (e.g., CASE statements within aggregate functions like MAX() or MIN()) to pivot the data and generate the desired output format. A dummy monotonically increasing column needs to be added.