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Team:NTNU Trondheim/Modeling
From 2011.igem.org
(Difference between revisions)
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=== Bayesian Hierarchy === | === Bayesian Hierarchy === | ||
We then wish to model the reliability for the observations... That is the probability of false positive/negative results | We then wish to model the reliability for the observations... That is the probability of false positive/negative results | ||
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Having the observations from the lab | Having the observations from the lab | ||
| - | + | "\mathtbf{x} = (x_{1} , x_{2} , \cdots , x_{n})" | |
were x_i is under condition C = 1 (stress) , and y_j is under condition C = 0 (no stress). | were x_i is under condition C = 1 (stress) , and y_j is under condition C = 0 (no stress). | ||
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=== Linear Classification === | === Linear Classification === | ||
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==== Non-linear Classification ==== | ==== Non-linear Classification ==== | ||
Revision as of 07:58, 29 June 2011
Models are under construction -------Page
3 types of models: Systems of ODE, Bayesian hierarchy and linear classification problems (LDA or similar). To be continued....
Contents |
Model Introduction
-What to model
-How to model
The Models
Systems of ODE
Bayesian Hierarchy
We then wish to model the reliability for the observations... That is the probability of false positive/negative results <math>P(RTF = 1|stress) ^{T}</math> and opposite. Having the observations from the lab
"\mathtbf{x} = (x_{1} , x_{2} , \cdots , x_{n})"
were x_i is under condition C = 1 (stress) , and y_j is under condition C = 0 (no stress).
