hello getting this error " module 'sklearn.utils._openmp_helpers' has no attribute '__pyx_capi__ " while running from mlxtend.feature_selection import SequentialFeatureSelector as SFS
Brother answer me one thing, why you people always take n=binary classification problem, why dont multiclassification problem. You all take such example which is every where. What is unique thing in your tutorial....?Answer is Nothing.
Brother dont take my comment in wrong way, spend some time in explaining each section of code pieces by pieces then it is more effective and this video is incomplete few more requirements must be there.
Hi I never mind. Everyone has their own perceptions so may be you are looking more information and might be someone only looking summarised information so it depends on person to person. Here I only create video how you can start any methods or algorithm but here if I will explain each and every steps in more details than might be duarion will be to long for video. I can explain each piece of code in depth but I am sure there will be very few viewers who look that because coodiing is not a racket science any body can do coding but need to understand the how you can apply any methods. But thanks for your feedback atleast you gave your some valuable time here otherwise people just watch the video and never share any feedback. Feedback is part of improvement so thank you again and will try to add more information in my next videos.
nice explanation. its a lot better than reading the documentation (just starting to dive in this data-related world). valuable video
Please, we need end to end projects for supervised and unsupervised learning. Thanks for all your good work.
Thanks for your suggestion. I will come back soon.
Thanks
Is the accuracy score you got during sfs selection is on test set or on train set??? bit confused because you did not fit on test set
Hi, can you make a video on how to use feature selection for unsupervised model? Thank you.
Thanks for your feedback.
Sure will create this video and thanks for good suggestion...
great explaination!
but why your cv value is 0?
Took just to save the time otherwise you can use CV= 5 or as per your requirement.
cv=5 or cv=10? which one is better value sir? for the SFS
We can not blindly use 5 or 10 .It's depends on many factors. so gerenally we use gridsearch to get the best value of CV.
Hello, it's a nice explanation. could you please explainRecursive feature elimination as well. thank you.
Thank you. I checked I had noted down this video but somehow I missed this. Surely will make it for you.
hello getting this error " module 'sklearn.utils._openmp_helpers' has no attribute '__pyx_capi__ " while running from mlxtend.feature_selection import SequentialFeatureSelector as SFS
Heyy,I am getting negative score after running SequentialFeatureSelector what should i do??
@Atul
Can you please share you code to me then I can check what mistake you did.. send me over my gmail atulapatelds@gmail.com
Brother answer me one thing, why you people always take n=binary classification problem, why dont multiclassification problem. You all take such example which is every where. What is unique thing in your tutorial....?Answer is Nothing.
Thanks for your feedback Next time will try to pick the multiple class problem and will try to make it unique...
Brother dont take my comment in wrong way, spend some time in explaining each section of code pieces by pieces then it is more effective and this video is incomplete few more requirements must be there.
Hi I never mind. Everyone has their own perceptions so may be you are looking more information and might be someone only looking summarised information so it depends on person to person.
Here I only create video how you can start any methods or algorithm but here if I will explain each and every steps in more details than might be duarion will be to long for video. I can explain each piece of code in depth but I am sure there will be very few viewers who look that because coodiing is not a racket science any body can do coding but need to understand the how you can apply any methods.
But thanks for your feedback atleast you gave your some valuable time here otherwise people just watch the video and never share any feedback. Feedback is part of improvement so thank you again and will try to add more information in my next videos.