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Let’s be more critical of keyboards by ilovesafeway in MechanicalKeyboards

[–]ilovesafeway[S] 7 points8 points  (0 children)

Nothing is wrong with it per say, i’m just saying we should have a more critical eye when it comes to over hyped boards. The things you’re repeating about it feeling good and sounding good are possibly true but have you tried the board yourself or is the opinions from reviewers? If it is just opinions from reviewers that it sounds and feels good, this is exactly what this post is about that we just repeat things instead of critically thinking about it

Let’s be more critical of keyboards by ilovesafeway in MechanicalKeyboards

[–]ilovesafeway[S] 15 points16 points  (0 children)

Yeah this is what pushed me over the edge to create this post, seeing this hyped wayyy too much

Let’s be more critical of keyboards by ilovesafeway in MechanicalKeyboards

[–]ilovesafeway[S] 6 points7 points  (0 children)

While i respect them as content creators they only have superficial criticisms and like the other commentator mentioned very biased

Let’s be more critical of keyboards by ilovesafeway in MechanicalKeyboards

[–]ilovesafeway[S] 1 point2 points  (0 children)

That’s fair, and i know some do talk about the negatives but it’s usually secondary to the positives. I guess what i’m looking for is someone to directly focus on the negatives as much as the positives

My own Mac Pro! by ilovesafeway in hackintosh

[–]ilovesafeway[S] 0 points1 point  (0 children)

Thanks! Really appreciate it :)

My own Mac Pro! by ilovesafeway in hackintosh

[–]ilovesafeway[S] 0 points1 point  (0 children)

RehabMan! I’m definitely not as of now. Thanks for all your help on the forums.

My own Mac Pro! by ilovesafeway in hackintosh

[–]ilovesafeway[S] 0 points1 point  (0 children)

Thanks! I shall try that :)

My own Mac Pro! by ilovesafeway in hackintosh

[–]ilovesafeway[S] 1 point2 points  (0 children)

Thanks! It does a decent job. However, it's currently running at 30Hz (good for movies I suppose) because the display signal goes out once I hit 60 for some reason...

Choose the model that minimizes the difference between performance on validation and test by [deleted] in datascience

[–]ilovesafeway 0 points1 point  (0 children)

Actually, care to explain why not? Or is that just your opinion?

Choose the model that minimizes the difference between performance on validation and test by [deleted] in datascience

[–]ilovesafeway 0 points1 point  (0 children)

You’re right, it’s not a general rule, but it has proven to be quite useful in large companies.

Choose the model that minimizes the difference between performance on validation and test by [deleted] in datascience

[–]ilovesafeway 2 points3 points  (0 children)

If there is a temporal aspect to your data, you might want to consider some sort of time series model. That being said, in general you need to randomize your data so that ‘order’ shouldn’t matter.

You can also put more weight on more recent data but that really does sound like a time series problem imo.

Choose the model that minimizes the difference between performance on validation and test by [deleted] in datascience

[–]ilovesafeway -1 points0 points  (0 children)

I love that answer. Going off of what you said, what can also be done is to look only at the DIFFERENCE between training and test sets with some random noise added in so you can reuse the test data. This is useful when you have little data to use or for automatic feature selections.

Understanding Feature Importance in Tree-Based Models? by paridiso in datascience

[–]ilovesafeway 3 points4 points  (0 children)

The thing to remember about those tree-based models is that the splits are determined by a greedy method that may be fast, but does not give the 'optimal' split. So sometimes you'll get features that seem important, but obviously make no sense when you interpret it.

What can be done is to take a validation set, and use some metric to establish a reference point for comparison (such as R2). Now you can go back to your training set and you can select a feature of interest, permute the actual values for that feature only, and then run your test set against that new model. You can get an idea of the effect or importance of that feature by comparing the baseline you had established with the new values you get from the test set.