We performed a comparison between Oracle Advanced 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."Ability to pull together multiple sources of information."
"The dashboard interface is intuitive and the user is able to interact with it to receive good results from the analytic."
"When needed, we will work closely with Oracle support and implement their workaround in our application."
"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."
"It doesn’t cost anything to use the product."
"I mainly use this solution for the regression tree, and for its association rules. I run these two methodologies for Weka."
"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 is a very nice tool, it needs very small requirements. If I want to implement something in Python, I need a lot of memory and space but Weka is very lightweight. Anyone can implement any kind of algorithm, and we can show the results immediately to the client using the one-page feature. The client always wants to know the story. They want the result."
"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."
"In Weka, anyone can access the program without being a programmer, which is a good feature since the entry cost is very low."
"The interface is very good, and the algorithms are the very best."
"The performance, scalability and queries should be addressed, as well as the data distribution of certain data techniques."
"Could use some refinement getting things that are not standard cloud applications, but more customized."
"There are some transactions we have not been able to find through the dashboard."
"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."
"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."
"While it might offer insights for basic warehouse tasks, it falls short of deeper understanding and results."
"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."
"Not particularly user friendly."
"In terms of scalability, I think Weka is not prepared to handle a large number of users."
"A few people said it became slow after a while."
"Weka could be more stable."
Earn 20 points
Oracle Advanced Analytics is ranked 7th in Data Mining while Weka is ranked 2nd in Data Mining with 14 reviews. Oracle Advanced Analytics is rated 8.0, while Weka is rated 7.6. The top reviewer of Oracle Advanced Analytics writes "Helpful technical support, but performance and queries should be addressed". On the other hand, the top reviewer of Weka writes "Open source, good for basic data mining use cases except for the visualization results". Oracle Advanced Analytics is most compared with IBM SPSS Statistics, whereas Weka is most compared with KNIME, IBM SPSS Statistics, IBM SPSS Modeler, Splunk User Behavior Analytics and SAS Analytics.
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