Today, I gave session at Advanced Technology Day conference in Zagreb. It was very excited to see full room of people at the presentation, mostly developers from .NET world interesting in R and Data Science. This is good sign that the Data Science and the R are becoming more and more popular at daily basis. Most popularity for the R will bring R Tool for Visual Studio, which means the R language became member of the family of the Visual Studio.
For those who was asking about my slides and demo sample here is the information:
- Presentation slides can be downloaded here,
- Source code of the demo is hosted at git hub at: http://github.com/bhrnjica/R-Workshop
- For more information about R , you can see my YouTube channel about R and Machine Learning at this link.
See you next time!
This is the third beta version of the GPdotNET v4.0 which brings new features and continuation of the new set of solvers. Beta 3 introduce Genetic Programming Multi-class Solver (GPMCS).
The latest version of the project can be found at http://github.com/bhrnjica/gpdotnet.
As announced in Beta 1 and Beta 2 there are new set of solvers. Beta 3 finally brings GP Multi-class solver, and announced feature complete of the GPdotNET v4.0.
Here is a quick recap of all new features announced in the last three beta versions:
1. New Start Page will be extended with new examples of Neural Nets : – binary classification, – multi-class classification and – regressions examples.
2. Improved module for loading experimental data, which now supports non numeric data like categorical or binary data. New data module also support normalization of the experimental data, handling missing values.
3. Introduction of the ANN solver for all three kind of problems:
4. Depending of the output column of loaded experimental data, different learning solver can be selected.
5. Introduction of the GP Binary class solver.
6. Introduction of the GP Multi-Class solver. In the flowing text you can see few screen shots:
Picture below shows loaded “iris flower data set” in to the GP multi-class solver.
The picture below shows GP Multi-class solver in action. As can be seen best solution is found at 242 iteration, with very high value of the fitness value.
Even better the prediction page shows how best chromosome predict iris value. As can be seen best solution predicts 13 rows correctly, and only 2 row are calculated wrong.
The last picture shows the Best Chromosome (solution) for the Iris Flows Data Set :
Since now the GPdotNET project is located at http://github.com/bhrnjica/gpdotnet.
Download GPdotNET v4 beta2
The last few days I am preparing the new build for publishing of GPdotNET v4.0 which will include lot of new features. In the last post I have announced ANN modul and compleately new modul for preparing tha data for modelling. Here is a quick overview of the new features comming in this build:
- Since this build the GP modul is also integrated with the new way of data preparation. Now with the latest version of GPdotNET the user will have the same user experience in modelling with GP and ANN.
- The big news for this build is ability for modelling classification problems (two-class as well ) with Genetic programming. Multy -classs GP solver will be released soon.
- Separation of the previous and new version. Both are included in the latest build.
- Disable protected operations.
As picture shows below you can choose models from prevous version on the left side. On the right side of the new model dialog, you can select modeling and prediction with ANN or GP.
After you select the solver GPdotNET is ready to accept the data.
From the previous blog post you can see more info about loading and handling data. The same user experimence you can see regadles of the solver type (ANN or GP).
Beside this GP integration there are several bug fix which were reported from the users.
In GP solver the new feature has been added: Ability to disable protected operations. In the previuous version of GPdotNET protected operations (eg. /, log, ln, etc) are enabled in the model. Whenever operation was undefined for the current value. GPdotNET returned default value (0 or 1). So with protected operation the model is always defined. With protected operations we collect much good genetic material dufirng evolution. In case the option is disable any upprotected operation can discar the model. This option is available in new and previous GP solver.
Features not implemented in this beta
1. Exporting GP/ANN model
2. Open/Save gpa file for new Solvers.