hi i want to classify skin pixel based on thier intesity in normalize rgb space i use only 2 channel for r and g as attached i was wondering if i train this by PC method how can i use it to make a decision(or get posteriori) if the pixel is skin given the r g ??
thanks
evaluation based on continious variable
evaluation based on continious variable
- Attachments
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- SkinCont.txt
- (1.72 KiB) Downloaded 464 times
Hi Mark thanks for quick response
the reason skin is 1 cos I inputted grand truth data(positive samples) where i am confident that r g gives skin colour i.e. I set them all to 1, when I try to train this it gives error where I cannot train discrete parameter with continuous one so i came up with two solutions:
1- discredited the parameters and use value to evaluate the skin posteriori value for given r and g, example attached.
2-remove skin column and then use continuous variable r and g by PC method to learn the network but in this case I am not sure how to evaluate the network as I cannot evaluate the values in genie. When I try to add arc between one of the continuous node it gives says it cannot connect arc, example attached
Appreciate any clue.
the reason skin is 1 cos I inputted grand truth data(positive samples) where i am confident that r g gives skin colour i.e. I set them all to 1, when I try to train this it gives error where I cannot train discrete parameter with continuous one so i came up with two solutions:
1- discredited the parameters and use value to evaluate the skin posteriori value for given r and g, example attached.
2-remove skin column and then use continuous variable r and g by PC method to learn the network but in this case I am not sure how to evaluate the network as I cannot evaluate the values in genie. When I try to add arc between one of the continuous node it gives says it cannot connect arc, example attached
Appreciate any clue.
well i have tried that already and it does not work i get the same error that i can not use the continuous and discrete parameter together, however i have managed to get rid of this error by changing one of the skin value to 0.1 instead of 0, then even if i get that how do i make inference to measure the skin outcome only if I have “r†and “g†value in my case.
Thanks a lot I really appreciate it
Thanks a lot I really appreciate it
- Attachments
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- SkinCont.txt
- (2.09 KiB) Downloaded 447 times
Hi thanks for you answer but my real intention by this example is to understand how I can train the continuous parameter and evaluate it by value node (so if I have r g then how can i get posterior without discreting the parameters).when I try to connect the arc between value node and continuous nodes it would not let me to do that I really appreciate if u can answer this
Thanks
Thanks