Viewing a single comment thread. View all comments

WarmAppleNight t1_j962exi wrote

What's up with so many of the different-colored groupings having identical labels (e.g. the five adjacent clusters that are each labeled "crust pie"?)

13

yourmamaman OP t1_j9636kc wrote

Sees it is differences like: 'Cream cheese crust apple pie' vs 'No crust zucchini pie'. But because I could only label the cluster with common words in the recipe title it couldn't find common enough words

−3

AnonymousButIvekk t1_j968yra wrote

yeah sorry man, this post is dumb the way its been made. a lot better ways to visualise what you meant

16

yourmamaman OP t1_j969p9p wrote

For example?

−7

AnonymousButIvekk t1_j96bfsu wrote

what does the distance between them mean? color means nothing other than to differentiate groups, on the first look. what is the difference, if there even is any, between horizontal and vertical distances, why are they clumped together on the left and the right. why so many crusts, why does it say pie every time, it obscures preception of size.

literally anything would make more sense, this is a piece of bad modern art before it is a representation of data.

9

yourmamaman OP t1_j96g009 wrote

This is true.

Visualizations of high-dimensional data are hard to make intuitive since it attempts to plot a dataset with 768 dimensions in a 2-dimensional image. So the axes do not have a label, like in a PCA.

Honestly looking for a better way to do this

0

Bejoty t1_j96xvxp wrote

You can plot the PCA loadings to give viewers an idea about what variables are affected moving along each axis.

1

yourmamaman OP t1_j96ycog wrote

It's like a hundred different variables. Seems people try to make their recipes just a bit unique just to be different.

But good idea, maybe an example in the plot.

1