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."
"It is a modeling tool with helpful automation."
"The features that I have found most valuable are the Bayesian statistics and descriptive statistics."
"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."
"IBM SPSS Statistics depends on AI."
"SPSS can handle whatever you throw at it, whether your data set contains 10,000, 100,000, or a million objects. It's like the heavy artillery of analytical tools."
"The learning curve to using this product is not steep. The program is appropriate for those who do not have a lot of background in programming, yet have to perform basic statistical analysis."
"The most valuable features mainly include factor analysis, correlation analysis, and geographic analysis."
"It doesn’t cost anything to use the product."
"I like the machine algorithm for clustering systems. Weka has larger capabilities. There are multiple algorithms that can be used for clustering. It depends upon the user requirements. For clustering, I've used DBSCAN, whereas for supervised learning, I've used AVM and RFT."
"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 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."
"Weka's best features are its user-friendly graphic interface interpretation of data sets and the ease of analyzing data."
"Working with complicated algorithms in huge datasets is really easy in Weka."
"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 interface is very good, and the algorithms are the very best."
"There is a learning curve; it's not very steep, but there is one."
"I would like SPSS to improve its integration with other data-filing IBM tools. I also think its duration with data, utilization, and graphics could be better."
"The product should provide more ways to import data and export results that are user-friendly for high-level executives."
"Technical support needs some improvement, as they do not respond as quickly as we would like."
"The solution needs more planning tools and capabilities."
"Improvements are needed in the user interface, particularly in terms of user-friendliness."
"IBM SPSS Statistics could improve the visual outputs where you are producing, for example, a graph for a company board of directors, or an advert."
"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."
"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."
"I believe is there are a few newer algorithms that are not present in the Weka libraries. Whereas, for example, if I want to have a solution that involves deep learning, so I don't think that Weka has that capability. So in that case I have to use Python for ... predict any algorithms based on deep learning."
"While it might offer insights for basic warehouse tasks, it falls short of deeper understanding and results."
"Weka is a little complicated and not necessarily suited for users who aren't skilled and experienced in data science."
"The product is good, but I would like it to work with big data. I know it has a Spark integration they could use to do analysis in clusters, but it's not so clear how to use it."
"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."
"A few people said it became slow after a while."
"Within the basic Weka tool, I don't see many tools that are available where we can analyze and visualize the data that well."
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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