Rapidminer 5.0 Video Tutorial #2 - Building a Gold Classification Trend Model Part 1

[JolienJM]

Thanks a lot for these videos! They are extremely helpful!

[Guevara76]

Hi Tom Thanks so much for your time, if you're ever in Dublin, give me a shout and be a pleasure to buy you a pint! keep up the great work.

[neuralmarkettrends1]

Yep, awfully close to a coin toss.

[DodoStek]

Apparantly the chances of the GC going up or down are not dependent on any of the predictor variables.

[hnrylee]

@DodoStek I doubt it. I applied the same procedure on the video on two different breast cancer datasets, and for prediction sets I got all target variables with the same label, just like in the video. No offense, but I suspect that there's something missing or simply wrong in this tutorial.

[hnrylee]

@hnrylee 2 very important additions:

1- The video is still very helpful to get familiar with the software. Actually it is the most useful I could find.

2- I applied the same procedure in the video on the two benchmark classification sets I mentioned above with a neural net model with a single hidden layer consisting of 10 nodes, and the result? 100% accurate prediction.

I tried to apply the same (neural net approach) for the gold data sets but unfortunatelly they require a pre-processing for NNs

[MrSagarchinni]

thanks tom its a great help for a beginner like me

[magick93]

Thanks, really helpful and inspiring video.

[gtowfic]

Very helpful with important details! Thank you so much Tom. I will not miss a video :)

[masterinex]

hi..there.., awesome video. I was just wondering what do the roles ID and label mean when we classify the variables ?

[xtremerange]

Excellent. Really helps understand the flow in Rapidminer

[jmherrera00]

Great stuff indeed! way to go! thanx a lot for this material. It is of great help

[kevylyap]

Thanks a lot! It's great, especially for beginners like me.

[paulwhittaker99]

Thanks for that Thomas, you've given me an "in" to the software - really appreciate that, I'll be watching the rest of them!

[harkes12]

thanks

[richipal]

Great, thanks a lot.

[latlov]

very nice tutorial, thanks Tom! ... taking notes.

[whatgivesify]

wow ...you should really be tutoring my datamining class, u have made this understood even when i have not seen this software ever before! thank you

[clmorford2]

thanks for the help (-: