I have trained several model’s to predict/detect categorical values from dataset.
Now I want to see which model performs best under this two condition:
- Time complexity (Time to predict/detect)
- Space complexity (How much space(GPU/CPU) a model requires to predict/detect)
Some of the model’s I have used are given below
RF, CNN, MLP, RNN, LGBM, LSTM, KNN, GRU
From this I could find the best model that could use less time and less space while detecting/predicting particular case’s.
Could you explain this python codes / pseudo code?
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