We performed a comparison between IBM SPSS Statistics and Weka based on real PeerSpot user reviews.
Find out in this report how the two Data Mining solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The most valuable features are the solution is easy to use, training new users is not difficult, and our usage is comprehensive because the whole service is beneficial."
"Custom tables and macros: They allow us to create useful reports quickly for a broad audience."
"It has the ability to easily change any variable in our research."
"The most valuable feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can into multidimensional setup space. It's the multidimensional space facility that is most useful."
"Since we are using the software as a statistical tool, I would say the best aspects of it are the regression and segmentation capabilities. That said, I've used it for all sorts of things."
"The software offers consistency across multiple research projects helping us with predictive analytics capabilities."
"The most valuable feature is the user interface because you don't need to write code."
"The solution has numerous valuable features. We particularly like custom tabs. It's very useful. We end up analyzing a lot of software data, so features related to custom tabs are really helpful."
"The interface is very good, and the algorithms are the very best."
"Weka's best features are its user-friendly graphic interface interpretation of data sets and the ease of analyzing data."
"There are many options where you can fill all of the data pre-processing options that you can implement when you're importing the data. You can also normalize the data and standardize it in an easier way."
"The path of machine learning in classification and clustering is useful. The GUI can get you results. No programming is needed. No need to write down your script first or send to your model or input your data."
"Working with complicated algorithms in huge datasets is really easy in Weka."
"In Weka, anyone can access the program without being a programmer, which is a good feature since the entry cost is very low."
"It is a stable product."
"Weka eliminates the need for coding, allowing you to easily set parameters and complete the majority of the machine learning task with just a few clicks."
"The design of the experience can be improved."
"In some cases, the product takes time to load a large dataset. They could improve this particular area."
"If there is any self-generation data collection plan (DCP), it would be helpful in gathering data. It would also be useful if there is a function to scale it up to, let's say, UiPath and have it consolidate and integrate into a UiPath solution."
"Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance."
"I know that SPSS is a statistical tool but it should also include a little bit of analytical behavior. You can call it augmented analysis or predictive analysis. The bottom line is it should have more graphical and analytical capabilities."
"Technical support needs some improvement, as they do not respond as quickly as we would like."
"The reports could be better."
"Perhaps in terms of visualization. It's not really easy to do some data visualization, just simple, descriptive analysis in SPSS. I think that could be an area for improvement."
"While it might offer insights for basic warehouse tasks, it falls short of deeper understanding and results."
"Weka could be more stable."
"If there are a lot more lines of code, then we should use another language."
"A few people said it became slow after a while."
"Not particularly user friendly."
"Within the basic Weka tool, I don't see many tools that are available where we can analyze and visualize the data that well."
"Weka is a little complicated and not necessarily suited for users who aren't skilled and experienced in data science."
"The filter section lacks some specific transformation tools. If you want to change a variable from a numeric variable to a categorical variable, you don't have a feature that can enable you to change a variable from a numeric variable to a categorical variable."
IBM SPSS Statistics is ranked 3rd in Data Mining with 36 reviews while Weka is ranked 2nd in Data Mining with 14 reviews. IBM SPSS Statistics is rated 8.0, while Weka is rated 7.6. The top reviewer of IBM SPSS Statistics writes "Enhancing survey analysis that provides valued insightfulness". On the other hand, the top reviewer of Weka writes "Open source, good for basic data mining use cases except for the visualization results". IBM SPSS Statistics is most compared with Alteryx, TIBCO Statistica, Microsoft Azure Machine Learning Studio, IBM SPSS Modeler and Oracle Advanced Analytics, whereas Weka is most compared with KNIME, IBM SPSS Modeler, Oracle Advanced Analytics, Splunk User Behavior Analytics and SAS Analytics. See our IBM SPSS Statistics vs. Weka report.
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