Overall my experience with using RapidMiner was great. It allowed me to rapidly try out different machine learning models and compare each result with one another. It also allowed me to conveniently address my workflow without having to write code. It is a great tool for students and people without a strong programming background. Its well documented functions and strong community addresses what ever questions I had with the processes.
One of the daunting requirements for data scientists and data storytellers is learning a programming language such as matlab and python and writing code for their tasks. This is on top of having to analyze and learn complex algorithms needed for the task. This can be a time consuming problem, especially for those who are not adept at programming. However, this is now a thing of the past because of RapidMiner Studio.
This is because RapidMiner features are drag and drop visual interface which makes all the difference. Data preparation to the final output and visualization is as simple as dragging blocks of your workflow into a canvas and connecting them altogether.
RapidMiner Studio also has most of the machine learning models used in the academe and the industry. One of the difficulties when dealing with code is tweaking the parameters of these models but because of the visual interface, you could simply click on the process and update this.
RapidMiner is also well documented. Each of the processes has their description, input, output, and parameters well described. Tutorial videos as well as blogs are available on their website. And finally, RapidMiner Studio has a community of data scientists that can help you when you have a question.
What I found to be very inconvenient is that the application crashes at times. This may be a problem limited to my own machine.
Aside from this I found that the application seems to hog my computers memory and cpu resources. This may be because the application is running on Java (VM). This may not be a problem for people with a higher spec machine.
I also found that the application lacks collaboration features which may be something that they could improve on in the future.
Great data analytic and visualization tool!
No coding skills needed! Rapidminer is a GUI tool that you can connect boxes on a canvas to conduct data anlysis, this serves as a great introduction to data analytics.
Free for students! You can get a provisional liscence with a dot edu account. This is a great perk of the software.
Data analytics and data visualization tools are available within the software with a plethora of other features!
Very buggy! The software tends to crash often, this is especially more common with things such as neural networks etc.
Limitations of some versions! Even with the student version there is a limit of 10,000 rows of output, so if you are trying to do analysis on a 12,000 point data set , 2000 points will randomly be omitted.
Started using this software a few months ago, and its shear power is amazing. The number of things the user can do with this software are amazing
Sometimes, while handling big data, like having large number of examples and attributes, it takes a lot of time. The cumulative time increase, when the user is optimizing manually different attributes based on the results
I learnt how to do data mining with this software. I can only say it is perfect even for new learners. When I started data mining the concept itself was new to me and I did not want to do complicated programming to do my data mining. That is why I chose RapidMiner. It is so easy to use and it provides lots of hint how to use each icon. I really prefer RapidMiner if I want to get my data mined faster and easier. Highly recommended.
The help section was not %100 complete. It has many explanation but examples are not good explained.
Very comfortable to use especially for a beginner and since it can be supported in any platform and excellent form of teaching.Makes machine learning easy
A bit pricey to acquire but worth it at the end and it can consume a lot RAM sometimes your computer freezes
I use RapidMiner for data analytics, data mining, classification and clustering in construction management.
1- Friendly interface, robust software operation
2- Easy to learn
3- It support several data types
Graphic plotting capabilities compare to R is low, I think this important feature that make RapidMiner stronger.
I'm using the basic version but was surprised to be able to easily analyse my small data set and identify a few interesting trends very swiftly.
Usually I'd do basic analysis manually with SQL and gnuplot, but can see myself using to Rapidminer more in future (not something I thought I'd say)
Provides a surprising array of different analytical templates from to off. Very easy to get up and running, an online tutorial videos quickly show how to use the different analytical reports.
I always prefer free versions of software to be open source, but that's perhaps being too picky.
I used RapidMiner a lot for doing proof of concept of some machine learning models before going to the production. It is really easy to construct a machine learning workflow, including loading data, features selection and cleaning, applying machine learning models and visualization. Sometimes, RapidMiner does not work well with big data as it requires a lot of memory to process the data. However, for me, it is the best tool yet to do pre-production experiements.
Easy to use.
Perfect for non-technical users.
RapidMiner includes a lot of Machine Learning libraries and algorithms.
Easy to construct simple and understandable machine learning workflows
Does not scale well with the big data.
Some visualization techniques are ambiguous.
It's a good platform while applying predictive analytics on any dataset with a user friendly interface to have the true picture of the future.
Visual workflow designer is the best part for predictive analytics.
I really like drag n drop interface for generating models.
Prebuilt templates are quite useful.
It's not always free. You need to purchase it if you wana work with more than 10000 rows.
Its processing becomes too slow (almost hangs) while working with terabyte or petabyte of data.
Sometimes, it becomes difficult to handle hundreds of models available.
I had a big data set I should analyze and didn't have any clue about data mining that's where I was introduced with rapid miner and I analyzed my data in less than a day. so I can just say its so easy and pretty simple and perfect.
I couldn't find any instructions and manual as a guideline for using it.
This tool is basically identical to Alteryx, but substantially cheaper - making it a better value pick
This tool only worked well for my teammates who are in Windows....anyone who was using Mac had consistent issues (even after reinstalls), making it hard to pick for a team that uses both Windows and Mac
I combined RapidMiner with R and it is a wonderful tool. It is the best in the market to build useful information from the result of data ming process.
Easy of use, fast, really nice presentation of results.
The expansion through code is not easy. It has a lot of functionalities but in some locations you got stuck and need to implement in other way.
It allowed us to do predictions on our data without having to be an experienced Data Scientist
It's so intuitive and easy to use. You can have a machine learning model built in just minutes and the price is great too! The best thing is that I don't have to be an experienced Data Scientist to work with this too. It's a great tool at a great price and very easy to use compared to other tools on the market!
Easy to transform data and model
easy to use machine learning algorithms
Options for feature customization
webservice is difficult to use
the GUI is not aesthetic