RapidMiner as Educational Data Mining Tool
August 29, 2018
RapidMiner as Educational Data Mining Tool
Score 9 out of 10
Vetted Review
Verified User
Overall Satisfaction with RapidMiner Studio
We use RapidMiner as the central data science platform to teach data analytics and machine learning. We are using RapidMiner for real-world analyses. Currently, to the best of my knowledge, only my department is using RapidMiner for teaching while others are using R, SPSS or WEKA for educating data mining. Our business is in education, and therefore, our primary concern is finding the most effective way of learning analytics – both data handling and algorithms.
- The RapidMiner provides a rich set of Machine Learning algorithms for Data Mining tasks, along with a comprehensive set of operators (functions) for data pre-processing. RapidMiner has a repository containing hundreds of machine learning algorithms and functions.
- RapidMiner is easy to use because RapidMiner is a user-friendly visual workflow designer software. Visualization of the process really helps users with data preparation and modelling. It makes my job easier in teaching machine learning and predictive analytics because I can show them the role of each operator and which one is vital in getting the right model. Students can directly see and understand the effect of using specific algorithms and functions after a few clicks, drags and drops. RapidMiner is something quick and easy to master.
- It is FREE! RapidMiner is available for free for educational use. I have been using RapidMiner for about three years, and I have never encountered any problem in renewing my license. The Educational Program License lasts for a year. My students have never complained about RapidMiner as the customer support is very efficient.
- RapidMiner Marketplace: If there are 'missing algorithm' from the RapidMiner library, we always can install extensions from the RapidMiner Marketplace. For example, I can access an extra about 100 additional modelling schemes after installing the WEKA extension. What ever the tasks are, if the required algorithm or functions are not available in the RapidMiner repository of ML algorithms, I can always find it in the marketplace.
- I hope RapidMiner would be the first data science platform that allows data scientists to change the behaviour of a machine learning algorithm that already exists in the repository. For example, I want to be able to change the way a genetic algorithm mutates.
- Automatic programming: One day, I hope RapidMiner can automatically generate codes in any 4th generation programming language based on the developed model.
- More tutorials/samples needed: Why doesn't RapidMiner becomes the next 'UC Irvine Machine Learning Repository'? Provide real examples and real cases for users to study and understand the best practices in modelling. RapidMiner already has some datasets for a tutorial. Besides the existing samples, I hope RapidMiner can provide more sample data and examples.
- As an educator, I do not seek a monetary return on any investment. What we seek as a lecturer is by looking into the outcomes like greater student learning, higher grades, or an increased number of students enrolment. Since RapidMiner is FREE for education, the first outcome I see is RapidMIner has enhanced learning and teaching analytics. Students become excited to learn analytics because they have the opportunity to use RapidMiner which is known to them as an expensive global brand and sophisticated tool.
- The second outcome is time spent to learn using an analytic tool become shorter compared to the previous platform. Therefore, we can learn more about other aspects of data analytics rather than focusing on how to use a tool.
- The third outcome is the program reputation. According to a study conducted by Maureen A. Conard, Sacred Heart University, has found that two variables, large percentage of graduates in successful careers and up-to-date technological facilities, were rated as very likely to be associated with very good academic reputation. RapidMiner is a Leader in the 2018 Gartner Magic Quadrant for Data Science and Machine Learning Platforms. Therefore, associating our academic program with the international brand like RapidMiner has enhanced our academic program reputation.
The other product like RapidMiner Studio that I have used is WEKA. I decided to use RapidMiner because almost all modelling methods and feature selection methods from the Weka machine learning library are available within RapidMiner. Furthermore, RapidMiner Studio is a visual workflow and therefore it is easier to demonstrate and visualise the processes involves in getting the desired results. Visualization of workflow enhances teaching and learning. RapidMiner is rich with algorithms and online learning materials that can assist students in their self-directed learning on data preparation, machine learning, deep learning, text mining, and predictive analytics. Moreover, RapidMiner repository has more than 1500 machine learning algorithms and functions that students can explore for any case study and assignments. The RapidMIner is also an open platform that can seamlessly integrates with other applications programmed with other programming languages like R and Python.