19 Juli 2011 8:33
I defined a model which I infer a binary discrete variable (range = 2). in some cases it happened that the sum of the probabilities of the two states was not 1.I am attaching two Example, one correctly inferred values and those in the wrong way.
prob_p0 prob_p1 5.01E-66 6.23E-67 1.53E-67 1.16E-70 9.12E-49 1.42E-43 4.25E-47 1.10E-48 3.14E-78 1.22E-75 1.59E-46 5.98E-50 3.25E-39 2.87E-48 4.19E-56 1.27E-52 2.97E-43 3.83E-34 1.33E-51 2.59E-49 1.02E-35 1.25E-42 7.41E-46 2.63E-43 1.07E-42 4.14E-32 8.00E-63 6.55E-70 5.24E-35 2.24E-40 9.50E-46 3.69E-41 2.41E-64 7.36E-66 1.15E-46 5.41E-55 2.05E-55 2.62E-47 1.62E-54 3.62E-55 2.21E-42 3.40E-45Correct
prob_p0 prob_p1 1.36E-82 1 5.95E-78 1 2.30E-75 1 4.14E-38 1 2.47E-77 1 2.89E-74 1 1.53E-60 1 4.43E-53 1 5.94E-70 1 1.24E-80 1 1.15E-79 1 3.45E-49 1 1.16E-73 1 1.45E-35 1 1.26E-48 1 7.55E-49 1 6.73E-60 1 3.07E-56 1 2.79E-66 1 2.23E-39 1 4.95E-82 1
19 Juli 2011 14:35Pemilik
What is your model and data?
20 Juli 2011 11:32I implemented three models:
- Naive Bayes
- Tree augmented naive Bayes (TAN)
- Hidden Naive Bayes
in all three models I have this problem with different frequency
the dataset is composed of a thousand files of different lengths.
As soon as I find a stable error I will share the code.