DEEP LEARNING
HELLO everyone please if someone can help me to find the solution for my question
i use deep learning model in rapidminer but the problem when i get the results and save it in excel sheet and do my work on it till now i am good
but when i try apply same model again with same deep learning i get another results not same first one with out any change everything
also when i try to do same thing and apply third time i get other results different than the first and second apply
please can i know why and how i will get the same result in same apply with out change
thank you a lot
i use deep learning model in rapidminer but the problem when i get the results and save it in excel sheet and do my work on it till now i am good
but when i try apply same model again with same deep learning i get another results not same first one with out any change everything
also when i try to do same thing and apply third time i get other results different than the first and second apply
please can i know why and how i will get the same result in same apply with out change
thank you a lot
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I assume that you are using a built-in Deep Learning operator. If you are using a Deep Learning extension, you will find a similar solution. There are two issues that you may need to deal with.
First is to do with splitting data for training and validation / testing. The Split Data operator uses a random process so that your data set is sub-divided into partitions in an unexpected way. However, if you select Advanced Parameters option, you will see a "use local random seed" option which allows you to "fix" the randomness so that it always splits data in the same way - this can be achieved by entering a specific number as a "local random seed" (any number, e.g. 2020).
The second issue is with the Deep Learning operator, which also uses a random process in the neural network learning. Again you can "fix" it by selecting a "reproducible" option, which reveals a "use local random seed" option, which can be selected and which allows you to define a random seed (e.g. 2020), so that your network will always learn from your data in exactly the same way.
Jacob
you are the best thank you a lot i did you are right
but last thing why i use 2020 and what the benefit for this for example why not another value more or less what will be different
please explain to me this value thank you alot
but last thing why i use 2020 and what the benefit for this for example why not another value more or less what will be different
please explain to me this value thank you alot
The value is arbitrary, so I suggested 2020, but any value will do. The idea of a specific value is that it is used as a random seed, i.e. it will initiate generation of a specific sequence of random numbers to guide all random processes in RapidMiner, e.g. selecting examples for a training / testing data partition. If the next time you (or your colleague) will use exactly the same random seed, you (they) will get exactly the same results.