"The supervised models are valuable. It is also very organized and easy to use."
"The most valuable features of the IBM SPSS Modeler are visual programming, you don't have to write any code, and it is easy to use. 90 to 95 percent of the use cases, you don't have to fine-tune anything. If you want to do something deeper, for example, create a better neural network, then you have to go into the features and try to fine-tune them. However, the default selection which is made by the tool, it's very practical and works well."
"It is a great product for running statistical analysis."
"Automation is great and this product is very organized."
"You take two quarters and compare them and this tool is ideal because it gives you a lot of visibility on the before and after."
"It's a very organized product. It's easy to use."
"Very good data aggregation."
"The GUI capabilities of the solution are excellent. Their Auto ML model provides for even non-coder data scientists to deploy a model."
"We value the collaboration and governance features because it's a comprehensive platform that covers everything from data extraction to modeling operations in the ML language. RapidMiner is competitive in the ML space."
"RapidMiner is very easy to use."
"The data science, collaboration, and IDN are very, very strong."
"It's helpful if you want to make informed decisions using data. We can take the information, tease out the attributes, and label everything. It's suitable for profiling and forecasting in any industry."
"Dimension reduction should be classified separately."
"The time series should be improved."
"Requires more development."
"When you are not using the product, such as during the pandemic where we had worldwide lockdowns, you still have to pay for the licensing."
"Time Series or forecasting needs to be easier. It is a very important feature, and it should be made easier and more automated to use. For instance, for logistic regression, binary or multinomial is used automatically based on the type of the target variable. I wish they can make Time Series easier to use in a similar way."
"Neural networks are quite simple, and now neural networks are evolving to these architecture related to deep learning, etc. They didn't incorporate this in IBM SPSS Modeler."
"It would be good if IBM added help resources to the interface."
"I would like to see all users have access to all of the deep learning models, and that they can be used easily."
"In the Mexican or Latin American market, it's kind of pricey."
"Many things in the interface look nice, but they aren't of much use to the operator. It already has lots of variables in there."
"RapidMiner isn't cheap. It's a complete solution, but it's costly."
"The biggest problem, not from a platform process, but from an avoidance process, is when you work in a heavily regulated environment, like banking and finance. Whenever you make a decision or there is an output, you need to bill it as an avoidance to the investigator or to the bank audit team. If you made decisions within this machine learning model, you need to explain why you did so. It would better if you could explain your decision in terms of delivery. However, this is an issue with all ML platforms. Many companies are working heavily in this area to help figure out how to make it more explainable to the business team or the regulator."
IBM SPSS Modeler is an extensive predictive analytics platform that is designed to bring predictive intelligence to decisions made by individuals, groups, systems and the enterprise. By providing a range of advanced algorithms and techniques that include text analytics, entity analytics, decision management and optimization, SPSS Modeler can help you consistently make the right decisions from the desktop or within operational systems.
RapidMiner's unified data science platform accelerates the building of complete analytical workflows - from data prep to machine learning to model validation to deployment - in a single environment, improving efficiency and shortening the time to value for data science projects.
IBM SPSS Modeler is ranked 7th in Data Science Platforms with 7 reviews while RapidMiner is ranked 6th in Data Science Platforms with 5 reviews. IBM SPSS Modeler is rated 8.6, while RapidMiner is rated 9.0. The top reviewer of IBM SPSS Modeler writes "Easy to use, quick to learn, and offers many ways to analyze data". On the other hand, the top reviewer of RapidMiner writes "Extensive features, Turbo Prep, Auto ML, good GUI and good stability". IBM SPSS Modeler is most compared with KNIME, IBM SPSS Statistics, IBM Watson Studio, Alteryx and Microsoft Azure Machine Learning Studio, whereas RapidMiner is most compared with KNIME, Alteryx, Microsoft Azure Machine Learning Studio, Tableau and DataRobot. See our IBM SPSS Modeler vs. RapidMiner report.
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