RapidMiner

Kommentare: 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.

Vorteile: 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.

Nachteile: 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.

Kommentare: Great data analytic and visualization tool!

Vorteile: 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!

Nachteile: 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.

Vorteile: 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

Nachteile: 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

Vorteile: 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.

Nachteile: The help section was not %100 complete. It has many explanation but examples are not good explained.

Vorteile: 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

Nachteile: A bit pricey to acquire but worth it at the end and it can consume a lot RAM sometimes your computer freezes