2 votes

What is "better-than-random" precision in clustering?

The authors mean to say that the achieved Precision is better than the baseline Precision we would get at random. For example, if we have 1000 examples with 200 being positive and 800 being negative, ...
  • 37.6k
1 vote

Using correlation as distance metric (for hierarchical clustering)

I'll expand a bit on the accepted answer to show that in case we've standard-scaled the input data (let's assume it's n-dim), then both euclidean and correlation based distance metrics are just scaled ...
1 vote

Is 'High School', 'Graduate', 'Unknown' ordinal or nominal data?

Education level is ordinal, as you already noticed. However, you cannot consider "Unknown" as one of the ordinal levels, it is missing data, so what you need to do is pick one of many ...
  • 124k
1 vote
Accepted

Is 'High School', 'Graduate', 'Unknown' ordinal or nominal data?

The variable Eduction with levels 'Uneducated', 'High School', 'College', 'Graduate', 'Post-Graduate' and 'Doctorate' is certainly an ordered categorical variable. Indeed, we all agree that these ...
  • 4,034
1 vote
Accepted

Probability that x-axis perfectly separates clusters

Yes, you are exactly correct. Here is an illustration, which also shows you can easily simulate questions like this one to sharpen your intuition: R code: ...
1 vote
Accepted

Do you use the PC1, PC2, PC3 or do you use PCA for feature selection in supervised learning?

I will try to outline a high-level answer to your points, even though there seems to be some confusion about what PCA is doing and how you can use it in your ML framework. PCA finds the components of ...
  • 150

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