In this tutorial, we highlight Rapidminer's weighting operator using an evolutionary approach. We use financial data to preweight inputs before we feed them into a neural network model to try to better classify a gold trend.
Video download link (HQ): Rapidminer 5.0 Video Tutorial #7
Calling all marketers! In this video we discuss how we can use Rapidminer to create a decision tree to help us find "sweet spots" in a particular market segment. This video tutorial uses the Rapidminer direct mail marketing data generator and a split validation operator to build the decision tree.
Video download link (HQ): Rapidminer 5.0 Video Tutorial #6
Its hard to believe but I'm already 50% done with my first batch of Rapidminer 5.0 Video Tutorials. So far, the reception has been positive and I thank everyone who emailed me, IM'd me, or commented on these tutorials. I made a promise to myself to make a batch of 10 video tutorials first before I re-engineer this website further.
So far so good and I'm on target to record a new video tutorial tonight or tomorrow morning. Video #6 will be about creating decision trees in Rapidminer for a direct mail marketing example. For video #7, I'll probably focus on an evolutionary weighting example, and then close out the remaining 3 tutorials with financial time series examples.
Below is an screenshot of one of the time series examples I'm working on. This is a time series chart of the S&P500 with a neural net generated trend line. Neat, huh?
In this video we continue where we left off in Video Tutorial #4. We discuss some of the parameters that are available in the Genetic Algorithm data transformers to select the best attributes in the data set. We also replace the first operator with another Genetic Algorithm data transformer that allows us to manipulate population size, mutation rate, and change the selection schemes (tournament, roulette, etc).
Video download link (HQ): Rapidminer 5.0 Video Tutorial #5
In this video I highlight the data generation capabilities for Rapidminer 5.0 if you want to tinker around, and how to use a Genetic Optimization data pre-processor within a nested nested experiment. Yes, you read that correctly, a nested nested experiment.
Video download link (HQ):Rapidminer 5.0 Video Tutorial #4
In this video I discuss how to use a cross and simple validation operator to split your training data into two sets: training and validation data sets. I also highlight the new intuitive “quick fix” error solution suggestions in Rapidminer 5.0. Enjoy!
Video download link (HQ): Rapidminer 5.0 Video Tutorial #3
See the Rapidminer 5.0 Video Tutorial #2 post for the data files used in this video
Looks like I'm on a roll! Please see my Rapidminer 5.0 Video Tutorial #2. In this video we begin the process of recreating my original written NMT YALE/Rapidminer tutorials into version 5.0 and into a video. This video shows how to import training and prediction data, add a classification learner, and apply the model, and get the results.
Video download link (HQ): Rapidminer 5.0 Video Tutorial #2
The data files you will need to follow along are Excel spreadsheets below:
Training data set: gold_final_input
Prediction data set: ga-gold
After a very long hiatus I present to my readers my first Rapidminer 5.0 video tutorial. Â Its just a quick 10 min introduction to the GUI and data import functions of Rapidminer 5.0. Â You’re gonna like the way it looks!
Video download link:Â Rapidminer 5.0 Video Tutorial #1
PS: I’m glad to be back guys. Leave me a comment if you want more, please stroke my fragile ego. LOL.
PPS: My Youtube Channel is here: Neuralmarkettrends1
PPPS: For those who want to follow along, see the original GE.xls file.
I consider myself a Bullish guy. I believe in the markets and that they’ll recover one day into another fabulous Bull Market. Heck, I’m still long in my retirement accounts and still plowing money into the markets as part of my long term investing strategy. However, there is a short term reality out there that any sane person can’t ignore. The markets are still sucking bad and this rally is probably going to fall apart now or around the 1000 level in the S&P500.
How did I come to this? I did it through three ways: Technical Analysis, my recently updated Rapidminer neural net classification model, and my Monte Carlo simulation model. You can check out my example classification model in the tutorial section to get an idea how to build one.
Bottom line: We don’t have the right ingredients in place for a new Bull Market and we have more lipstick to put on this pig before we build a new Bull Market.
I recently downloaded the new version of TraderXL and was surprised to see a major update to the ClassifierXL module (as part of the NeuroXL suite). I’ve used this module before to classify like groups of stocks and identify (per my requirements) the right stock to buy out of a group of many. Major updates to the module include a better GUI interface and the inclusion of five neural net functions, namely the Threshold, Hyperbolic Tangent, Zero-based Log-sigmoid, Log-sigmoid and Bipolar Sigmoid functions. 
To see what it can do, I’m attaching a recently classified ADR stock scan spreadsheet from www.aaii.com.I downloaded this scan from AAII, used the zero-based log-sigmoid scan, and classified the stocks into 5 similar groupings.After it crunched the data it created two charts and a color coded spreadsheet from your data.If you flip to the charts in the spreadsheet, you’ll notice that cluster 1 and 5 have large groupings of similar stocks.These clusters represent the most interesting of the stock groups and should clue in the data modeler to some possible opportunities in the data. Let’s say you are interested in investing in a China based company and you have lots of data from a stock scan to go through. How can you identify a good candidate for more due diligence? First open the spreadsheet and then using the pull down data sorting menus to select China as your country of choice. 
The data in the spreadsheet will sort and show 7 China based stocks, with 5 being in Cluster 1 and 2 being in Cluster 5. Now this is interesting data revelation to me because not all of these 7 China based stocks are being classified as the same. If you further drill down the data by selecting the Top 10 EPS Growth Estimate, then you are left with 4 China based stocks in Cluster 1: LFC, JOBS, BIDU, and MR. These 4 companies should give you a good smaller list of stocks for further review. 
Granted, this example was a fast way of doing a complex data analysis but the ClassifierXL module helped simplify the process. The neat thing about this module is that it does all the heavy lifting for you and organizes the data in an easy to use spreadsheet!
I’ve been thinking of holding a “Introduction to Rapidminer” webcast. Can any of my readers suggest a good webcast tool (free or pay)?
I don’t have any date in mind but it will have to either be before my vacation in December or after. I plan on going over the GUI, basic operators and experiment structure, and building a simple model from scratch.
Is there any interest out there for something like this? Please drop me a comment. Thanks.
My next Rapidminer Video Tutorial #4 on Evolutionary Weighting is done and needs to be cleaned up before I post it this weekend, so get ready for it. It’s one of the most intricate ones I’ve shared with my readers yet and will probably clock in over 20 minutes in length. We combine the lesson from the Genetic Feature Selection Tutorial and build a new experiment on top of it. It’s a “one click” evolutionary extravaganza!
I’m also planning on cleaning up my older videos and re-recording them using Camstasia. I’ll definitely be finishing my Introduction to Rapidminer Video Tutorial 1 & 2 over the coming weeks and plan on recording some new ones. All my old “Test Videos” will be deleted!
My new posting frequency has definitely helped my frame of mind and allows me to put more time into these videos. As always, thanks for visiting. Now would be a great time to subscribe to my feed!