RapidMiner is a software which useful where user don't want to code.

It is drag and drop based software.

Alot of library is there. Review collected by and hosted on G2.com.

It does not provide freedom like programming does.

We can not customize things easily by ourselves.

Also we can not take live data. Review collected by and hosted on G2.com.

I like the UI and the assortment of plugins/add ons. It was easy to install and had a ton of videos to support my use case. Support was good and answered my questions promptly. Review collected by and hosted on G2.com.

So far cannot find anything that stands out as a dislike. There is a bit of information overload and can be a bit overwhelming at first but it's acceptable. Making some improvements to the onboarding would be great. Review collected by and hosted on G2.com.

It's a user-friendly tool that allows data analysts and data scientists to run several ML models, statistical analyses and perform EDA on the same platform. Allows a variety of plugins for integration and is compatible with iOs & Android systems. Review collected by and hosted on G2.com.

Rapid Miner software is not cost-effective. It doesn't support customization of base models for Machine Learning. Searching operators proves to be challenging at times, considering the interface design. Review collected by and hosted on G2.com.

Visual process flow, comprehensive set of current analysis tools, cross validation, and sliders for scenario/what-if analyses. And all of this is free for academic use for both professors and students. Review collected by and hosted on G2.com.

Lack of learning resources available to get started from scratch. There are lots of videos, so this may be a non-issue for most learners. I prefer books and there is nothing except one Marketing Analytics textbook (Hair et al 2021) that is current, and uses rapidminer for some analyses. Review collected by and hosted on G2.com.

The tutorial is clear, giving the students a self-learning opportunity. The examples available are very well documented and the students can see a machine learning process working with a few clicks! Besides we have a lot of videos on the internet and many papers using Rapidminer to develop cases.

It is easy to create processes and explain machine learning as the students do not need to code anything (sometimes they are afraid of that! I can tell this because I teach Python to them too...).

The interface is clear, and the program provides us with a lot of detailed information about the operators in use.

It recommends the next operators to be used, helping the students to understand prediction inside the tool.

It is a very good practical environment for Business Intelligence courses too - we had this experience at Skema with almost 200 students this semester. All of them have installed and upgraded the version without problems. Review collected by and hosted on G2.com.

For my purposes, it fits very well. It takes a long time to start, but no problem at all. Review collected by and hosted on G2.com.

Very impressed with the variety of the algorithms offered by RapidMiner, which allow business analysts and data scientists to use robust algorithms across statistical and computational Review collected by and hosted on G2.com.

Have not found any point that I dislike. The only recommendation to RapidMiner is to keep updated with the most current algorithms available in the market, which can continue to sustain the extant success. Review collected by and hosted on G2.com.

Implementing ML algorithms is a difficult business. Rapid Miner makes it easy to load your data, check your data for missing values, erroneous values, and correct them - and to implement both simple and advanced algorithms to understand your data better and to draw insights. Review collected by and hosted on G2.com.

There are lots of learning materials - RM Academy, video tutorials, etc, but they tend to the theoretical and make it quite difficult to implement one's exercise.

The documentation within the program is really abstract and jargon-filled. I struggle when I read the functional labels and help explanations. Some of this is my own (beginner) level of expertise, of course, but I do think things could be spelled out more clearly and logically. Review collected by and hosted on G2.com.

Rapid Miner is a tool that is extremely easy to use. I especially appreciate its file handling capabilities and the immediate visibility of the data file I am working with. Even when I am tired or sick I can easily work with this program because of its drag-and-drop formula. There are many additional libraries that can be added if they are needed and it offers a wide range of available algorithms. I also like a lot of videos on You Tube which solved many of my problems. There are even courses on Coursera which teach data mining with RapidMiner. Review collected by and hosted on G2.com.

I had problems with the Operator library - after installation, it worked for a while and then stopped and informed me that it is not compatible with the main program. However, after re-installation it works again.

Of course, Rapidminer has some limitations compared to Python or own programs, but I love it for its simplicity. Review collected by and hosted on G2.com.

You can save the k-means clusters models and use them again to find out insights with several data. Review collected by and hosted on G2.com.

First, until the year 2015, Rapidminer was collaborative, but now it is licensed software. Review collected by and hosted on G2.com.

Great tutorials and excellent explanations. Easy to use data sets for learning. Excellent platform for those new to AI and for experienced pros is still very useful and easy to use. Very intuitive interface. Excellent product. Highly recommend. Review collected by and hosted on G2.com.

Some areas not completely explained how ceratin algos work or integrate with data. Review collected by and hosted on G2.com.