We performed a comparison between SAS Analytics and Weka based on real PeerSpot user reviews.
Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining."Modeling ones and figures, such as PROC LIFETEST, PROC LOGISTICS, PROC GPLOT. PROC FREQ and PROC MEANS, are also among the valuable features."
"It's very easy to use once you learn it."
"It has also been around for an extremely long time, has a strong history, and good market penetration."
"The team immediately resolves the issues."
"SAS Analytics plays a vital role in enhancing our decision-making processes, particularly in areas such as customer segmentation and operational efficiency."
"I like that it is quickly embedding interactive reports and dashboards into a website, Outlook Mail, or even a mobile app."
"The most valuable feature is the ability to handle large data sets."
"All of the data analytics features in SAS Analytics are valuable to us since we're using them daily across our entire analytics team."
"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."
"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."
"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."
"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."
"I mainly use this solution for the regression tree, and for its association rules. I run these two methodologies for Weka."
"Working with complicated algorithms in huge datasets is really easy in Weka."
"The interface is very good, and the algorithms are the very best."
"It doesn’t cost anything to use the product."
"They could enhance the AI capabilities of the product."
"Once a SAS figure is produced one would like to modify things, such as titles, legends, and incorporate risk sets as a footer on the plots."
"The graphing and visualization features could be enhanced, in my opinion. I would especially stress improving the visualization capabilities."
"Support at universities used to be limited, but I hear this is changing."
"The training for SAS Business Intelligence is often difficult to arrange. It is often cancelled due to not enough people being enrolled."
"There is potential for enhancement, particularly in the virtualized dashboard's capability to generate reports."
"I would like to see their interface to R added to either Base SAS or SAS Analytics."
"This solution should be made more user-friendly."
"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."
"Weka could be more stable."
"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."
"Weka is a little complicated and not necessarily suited for users who aren't skilled and experienced in data science."
"If there are a lot more lines of code, then we should use another language."
"While it might offer insights for basic warehouse tasks, it falls short of deeper understanding and results."
"Within the basic Weka tool, I don't see many tools that are available where we can analyze and visualize the data that well."
"In terms of scalability, I think Weka is not prepared to handle a large number of users."
SAS Analytics is ranked 5th in Data Mining with 11 reviews while Weka is ranked 2nd in Data Mining with 14 reviews. SAS Analytics is rated 9.0, while Weka is rated 7.6. The top reviewer of SAS Analytics writes "Provides comprehensive data analysis tools and functionalities, but its higher pricing and potential stability issues may present drawbacks". On the other hand, the top reviewer of Weka writes "Open source, good for basic data mining use cases except for the visualization results". SAS Analytics is most compared with KNIME, IBM SPSS Statistics, SAS Enterprise Miner and IBM SPSS Modeler, whereas Weka is most compared with KNIME, IBM SPSS Statistics, IBM SPSS Modeler, Oracle Advanced Analytics and SAS Enterprise Miner.
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