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."I've found the descriptive statistics and cross-tabs valuable. The very simple correlations and regressions are as well."
"Capability analysis is one of the main and valuable functions. We also do some hypothesis testing in Minitab and summary stats. These are the functions that we find very useful."
"The features that I have found most valuable are the Bayesian statistics and descriptive statistics."
"in terms of the simplicity, I think the SPSS basic can handle it."
"Most of the product features are good but I particularly like the linear regression analysis."
"The SPSS interface is very accessible and user-friendly. It's really easy to get information in it. I've shared it with experts and beginners, and everyone can navigate it."
"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 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."
"In Weka, anyone can access the program without being a programmer, which is a good feature since the entry cost is very low."
"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."
"I mainly use this solution for the regression tree, and for its association rules. I run these two methodologies for Weka."
"It is a stable product."
"The interface is very good, and the algorithms are the very best."
"It doesn’t cost anything to use the 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."
"With clustering, if it's a yes, it's a yes, if it's a no, it's a no. It gives you a 100% level of accuracy of a model that has been trained, and that is in most cases, usually misleading. Classification is highly valuable when done as opposed to clustering."
"The design of the experience can be improved."
"In developing countries, it would be beneficial to provide certain features to users at no cost initially, while also customizing pricing options."
"The solution needs to improve forecasting using time series analysis."
"I feel that when it comes to conducting multiple analyses, there could be more detailed information provided. Currently, the software gives a summary and an overview, but it would be beneficial to have specific details for each product or variable."
"SPSS is a tool that's been around since the late 60s, and it's the universal worldwide standard for quantitative social science data analysis. That said, it does seem a bit strange to me that the graphical output functions are so clunky after all these years. The output of charts and graphs that SPSS produces is hideous."
"Most of the package will give you the fixed value, or the p-value, without an explanation as to whether it it significant or not. Some beginners might need not just the results, but also some explanation for them."
"Better documentation on how to use macros."
"Technical support needs some improvement, as they do not respond as quickly as we would like."
"If there are a lot more lines of code, then we should use another language."
"In terms of scalability, I think Weka is not prepared to handle a large number of users."
"Not particularly user friendly."
"If you have one missing value in your dataset and this missing value belongs to a specific attribute and the attribute is a numeric attribute and there is only one missing data, whenever you import this data, the problem is that Weka cannot understand that this is a numeric field. It converts everything into a string, and there is no way to convert the string into numerical math. It's really very complicated."
"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."
"Weka is a little complicated and not necessarily suited for users who aren't skilled and experienced in data science."
"The visualization of Weka is subpar and could improve. Machine learning and visualization do not work well together. For example, we want to know how we can we delete empty cells or how can we fill in the empty cells without cleaning the data system and putting it together."
"Weka could be more stable."
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, SAS Analytics and Splunk User Behavior Analytics. See our IBM SPSS Statistics vs. Weka report.
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