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I have tried some of the algorithms like svm and knn but it seems too slow to run on my computer.
Are there any ways to make those algorithms running faster?
The text was updated successfully, but these errors were encountered:
Well...These algorithms are generally slow - anywhere you run them..
However, assuming you have a better implementation of the in python, you could use the python generic module that allows you to run your own algorithms (with your own backend).
You can also do your own processing in there - have a look at this thread too
Okay, I will try them then. Another problem is still on knn. I set n_neighbor: 2, 4, 8,16 for each model but seems the cv results are the same. They should be different right?
mae : 0.07718227001626582
mae : 0.07718227001626582
mae : 0.07718227001626582
mae : 0.07718227001626582
I forget to tell you that I used SklearnknnRegressor.
Okay, I will try them then. Another problem is still on knn. I set n_neighbor: 2, 4, 8,16 for each model but seems the cv results are the same. They should be different right?
mae : 0.07718227001626582
mae : 0.07718227001626582
mae : 0.07718227001626582
mae : 0.07718227001626582
I forget to tell you that I used SklearnknnRegressor.
do you run 'main_querry_v1.py' file success? I can't run it.
I have tried some of the algorithms like svm and knn but it seems too slow to run on my computer.
Are there any ways to make those algorithms running faster?
The text was updated successfully, but these errors were encountered: