Thanks for the video. I am working to create a project about clustering to build my R coding portfolio. I wish to can find job as data analyst finally.
@HeduAI5 жыл бұрын
Good luck! :) Have fun with the project!
@christianngameni15387 жыл бұрын
Perfect explanation. Thanks
@changyongkang76515 жыл бұрын
great, thanks for video
@MalayaliPada4 жыл бұрын
Well explained. Helped me with my homework :P
@hemalathagonuguntla8345 жыл бұрын
Thanks for the video.Your explanation is very good.I would also like to listen from you on how to determine the number of clusters.Thank you
@drisstaoufiki90705 жыл бұрын
Hi, randomly .
@hemalathagonuguntla8345 жыл бұрын
@@drisstaoufiki9070 Thank you
@agnesayuba51547 жыл бұрын
clear explanations. thanks
@brijeshdilipkumardave1937 жыл бұрын
Thax a lot!!!
@SameerKhan-ht4mx6 жыл бұрын
Can I get the dataset and code for this example?
@ThinkerHigh7 жыл бұрын
Amazing!
@danilomeireles15 жыл бұрын
MUITO BOM, GOSTEI DA EXPLICAÇÃO
@tapanvaishnav51147 жыл бұрын
can you post cluster results as per sepal width and height? Also, it's a bit hard to visualize the problem with four different variables, I mean this algo calculates the distance for clustering but say in actual scenario clustering only depends on petal width and length, How do we deal with those? Am I wrong somewhere, please elaborate.
@moovendhanm17194 жыл бұрын
I really attracted by your sweet voice...and I searched for more videos...but I ...
@mahnaz52173 жыл бұрын
how did you do the working directoriy ? i dont know how to copy paste it in R
@johanverm907 жыл бұрын
Perfekt!Thanks.Regards.
@abubakarali62795 жыл бұрын
Any useful source to learn DS.
@excelsior7597 жыл бұрын
The last statement "plot (iris).....", should it not be iris.features instead of just iris ?
@HeduAI7 жыл бұрын
"petal.length" and "petal.width" are iris dataset's features. So when I type , I am in fact calling its features. There is an easier way to do this. In R, rather than "." we use "$" to call columns of a dataframe. So I could have just typed the following to get the same result: plot( iris$petal.length, iris$petal.width)