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Thanks for sharing the implementation of OC-NN (a cool idea indeed). I tried the implementation of OC-NN from this file < https://github.com/raghavchalapathy/oc-nn/blob/master/src/models/OC_NN.py>. However, the results are quite unstable between multiple executions of the same code (keeping the same hyper-parameters and same random_seed=42). For example,
execution 1: f1 0.901
execution 2: f1 0.16
execution 3: f1 0.91
execution 4: f1 0.24
and so on.
Hello @raghavchalapathy ,
Thanks for sharing the implementation of OC-NN (a cool idea indeed). I tried the implementation of OC-NN from this file < https://github.com/raghavchalapathy/oc-nn/blob/master/src/models/OC_NN.py>. However, the results are quite unstable between multiple executions of the same code (keeping the same hyper-parameters and same random_seed=42). For example,
execution 1: f1 0.901
execution 2: f1 0.16
execution 3: f1 0.91
execution 4: f1 0.24
and so on.
I want to confirm if this is the correct implementation or should I look into this file: https://github.com/raghavchalapathy/oc-nn/blob/master/src/models/OneClass_SVDD.py as you have mentioned this file in a separate issue
Note: I trained OC-NN on my custom data.
Your response is appreciated.
Thanks,
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