Machine Learning Done Wrong

#1

Post by denzil_correa » Sat, Feb 28, 2015, 4:35 PM UTC

Machine Learning Done Wrong
ml.posthaven.com

Re: Machine Learning Done Wrong

#2

Post by trunkation » Sat, Feb 28, 2015, 9:39 PM UTC

Is it somehow inspired by Linear Algebra Done Wrong by Treil which itself was probably inspired by Linear Algebra Done Right by Axler ? :)

Re: Machine Learning Done Wrong

#3

Post by chengtao » Sat, Feb 28, 2015, 9:54 PM UTC

trunkation wrote: post #2

Is it somehow inspired by Linear Algebra Done Wrong by Treil which itself was probably inspired by Linear Algebra Done Right by Axler ? :)

Not really, it was actually more inspired by Statistics Done Wrong.

Re: Machine Learning Done Wrong

#4

Post by chengtao » Sat, Feb 28, 2015, 9:56 PM UTC

Also, thank you all for reading the post. I'm the author and I'll be happy to clarify any of the points in the blog~

Re: Machine Learning Done Wrong

#5

Post by [deleted] » Sat, Feb 28, 2015, 9:56 PM UTC

trunkation wrote: post #2

Is it somehow inspired by Linear Algebra Done Wrong by Treil which itself was probably inspired by Linear Algebra Done Right by Axler ? :)

[deleted]

Re: Machine Learning Done Wrong

#6

Post by trunkation » Sat, Feb 28, 2015, 10:06 PM UTC

chengtao wrote: post #3

trunkation wrote: post #2

Is it somehow inspired by Linear Algebra Done Wrong by Treil which itself was probably inspired by Linear Algebra Done Right by Axler ? :)

Not really, it was actually more inspired by Statistics Done Wrong.

Oh, Ok. Never knew there was a book by that title.

Re: Machine Learning Done Wrong

#7

Post by moultano » Sat, Feb 28, 2015, 10:07 PM UTC

I'm glad #1 is #1. If I had to partition these into two sets, they would be "make sure it works (2-7)" and "make sure your definition of 'works' works (1)."

Re: Machine Learning Done Wrong

#8

Post by antonb2011 » Sat, Feb 28, 2015, 10:08 PM UTC

You suggest up/down sampling rare cases. Can you please elaborate on the standard approaches for this kind of problem? For both linear and nonlinear classifiers. Thank you.

Re: Machine Learning Done Wrong

#9

Post by ai_maker » Sat, Feb 28, 2015, 10:10 PM UTC

Good post! A bunch of mistakes is a bunch of opportunities to improve. It kind of complements Domingos' paper:

http://homes.cs.washington.edu/~pedrod/papers/cacm12.pdf

Re: Machine Learning Done Wrong

#10

Post by mystique » Sat, Feb 28, 2015, 10:42 PM UTC

Good list. I am new to Machine Learning with only ~1 year of real work and sometimes I slip and make one of these mistakes.

I have a question on #7. I have not used the co-efficients to mean feature importance but some times get tempted to use them. How do you explain which factors are the most important factors behind some outcome to non-stat people?