I need a bayesian inference, using Markov Chain or Monte Carlo, in Python, to predict the next boxes colours based on past colours.
The past data has the following data:
Index, Begin timestamp, End timestamp, Box colour
1, 2019/05/14 15:10, 2019/05/14 16:35, Blue
2, 2019/05/14 16:35, 2019/05/14 17:01, Blue
3, 2019/05/14 17:01, 2019/05/14 19:50, Blue
4, 2019/05/14 19:50, 2019/05/14 21:00, Red
The program must be able to calculate the probabilities for next box and subsequents being blue or red:
- Next boxes
- Next 2 boxes
- Next 3 boxes
- and so on until 10 boxes
Must be easy to use as I´ll put the past N boxes and it must predicts the next boxes.
The final product for this project must be:
1 - The Python source code
2 - Final calculations (functions or parameters) that can be implemented in another programming language. The others languages doesn´t have library for bayesian calculations. So, maybe an algorithm can be generated to be implemented.
There is an example attached: boxcolors.csv.
The begin and end timestamps are in format DD/MM/YYYY HH:MM
24 фрилансеров(-а) в среднем готовы выполнить эту работу за $157
Hi there! I have experience working and coding some markov models as you are requesting. I have a question tough... is this part of some Univ. task?
My preferred method of freelancing is an interactive approach to project solving. I have an MSEE specializing in Digital Signal/Image/RF Processing. I do my work in MATLAB (expert). I also do Python programming.
Hey, I can do this for you cheap and easy within a day or two. Please give me this project as it will be my first paid project on freelancer.com.