[S1E3] Understanding K Nearest Neighbors Algorithms | 5 Minutes With Ingo
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- Опубліковано 27 січ 2015
- This week, Ingo Mierswa, RapidMiner's CEO, Co-Founder & Data Scientist in Residence, explains how the K-nearest-neighbors algorithm is used to formulate ideas by comparing points in a data-space and using the most similar data points as guidelines for predictions.
Plus, Ingo asks Data Scientist Number 7 to clean up Glen's mess, Doc Brown makes another split-second appearance and we hear the brief chuckle of a Python wearing a tuxedo.
DISCLAIMER: No data scientists were harmed during the filming of this episode. In fact, they were too busy doing amazing things with RapidMiner.
MUSIC CREDITS: Evil Thoughts, The Oscillator, James Taylor Quartet, Real Self Records, 2000 - Наука та технологія
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I've read elsewhere to learn more about kNN and this was by far the quickest and most simple explanation I have ever seen. Perfect guys, thank you!
Thanks, I'm studying k-NN at the moment. I like how the internet is giving us, the public, unprecedented access to the people who run the companies that we would never have had before. :)
Hey Ingo, these series of videos are amazing. Seriously.
Best wishes from Brazil.
that is an awsome explanation of KNN ,thanks guys keep it up
great! i can easily imagine how the algorithm works, thanks!
Arguably, the best way of explaining
Love the style :))
great starting !!
That was really nice
Echt gut und einfach erklärt!
interesting way to learn ML, good! Subscribed!
Great and interesting way to convey information
this really helped, i got a test in a two hours, i should do fine cause of you
good job guys... coool :)
Ingo is a legend :)
great way :)
you are awesome
Great video! However, I would like to see it from a mathematical perspective.
I love the intro! You needa create some thumbnails to justify your vids mang
Good explanation approach ... keep it up ...
Actually though a harder glass is more likely to break than a soft one.
Great video..
I have a problem...
Actually I already asked in rapidminer forum, but no one has given an answer yet..
community.rapidminer.com/discussion/55963/how-k-nn-algorithms-work-with-same-distance-in-rapidminer#latest
I can't find a satisfying answer for KNN-algorithm with same euclidean distance in rapidminer..
say k=5. Now I try to classify an unknown object by getting its 5 nearest neighbours. What to do, if distance is a lot of the same distance.. if after determining the 4 nearest neighbors, the next 2 (or more) nearest objects have the same distance and diferent label? Which object of these 2 or more rapidminer chosen as the 5th nearest neighbor?
I confused.. I try in excel, and the result is diferent with rapidminer for some data. in excel the result label is "LU":
i.ibb.co/RSYnTWg/Capturess.jpg
but the result in rapidminer is "LT" :
i.ibb.co/NKv0bmp/4.jpg
result rapidminer weighted vote is checked is "LU" :
i.ibb.co/r68y05v/5.jpg
How rapidminer work with case like that...
how rapidminer sorting the distance ?...
something wrong with my data ?, or rapidminer sorting random if distance is same ?
thanks in advance for your help
one like to the intentionally dropped mug.
The Eyrie :)
I just shitted in my pants :(
who was that haha guy?
And this has no help in my exam
Lol wanna be Data Scientist #8 in that company.
It's actually 6:28 and the guy holding the camera is talking too loud... maybe he should just stay mute.
it will be a great explanation if u just skip the bla bla of the horse .......
This shtick is terrible. Just teach me math.