IBM SPSS Modeler vs Weka comparison

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Executive Summary

We performed a comparison between IBM SPSS Modeler 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.
To learn more, read our detailed IBM SPSS Modeler vs. Weka Report (Updated: March 2024).
765,386 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"The quality is very good.""It will scale up to anything we need.""The most valuable features of the IBM SPSS Modeler are visual programming, you don't have to write any code, and it is easy to use. 90 to 95 percent of the use cases, you don't have to fine-tune anything. If you want to do something deeper, for example, create a better neural network, then you have to go into the features and try to fine-tune them. However, the default selection which is made by the tool, it's very practical and works well.""​It works fine. I have not had any stability issues; it is always up.​""The ease of use in the user interface is the best part of it. The ability to customize some of my streams with R and Python has been very useful to me, I've automated a few things with that.""New algorithms are added into every version of Modeler, e.g., SMOTE, random forest, etc. The Derive node is used for the syntax code to derive the data.""Very good data aggregation.""Automation is great and this product is very organized."

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"The interface is very good, and the algorithms are the very best.""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.""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.""Working with complicated algorithms in huge datasets is really easy in Weka.""Weka's best features are its user-friendly graphic interface interpretation of data sets and the ease of analyzing data.""I mainly use this solution for the regression tree, and for its association rules. I run these two methodologies for Weka.""In Weka, anyone can access the program without being a programmer, which is a good feature since the entry cost is very low."

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Cons
"The time series should be improved.""When you are not using the product, such as during the pandemic where we had worldwide lockdowns, you still have to pay for the licensing.""The product does not have a search function for tags.""Dimension reduction should be classified separately.""C&DS will not meet our scalability needs.""The forecasting could be a bit easier.""We would like to see better visualizations and easier integration with Cognos Analytics for reporting.""Regarding visual modeling, it is not the biggest strength of the product, although from what I hear in the latest release it's going to be a lot stronger. That, to me, has always been the biggest flaw in using this. It's very difficult to get good visualization."

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"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 is a little complicated and not necessarily suited for users who aren't skilled and experienced in data science.""Weka could be more stable.""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.""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.""In terms of scalability, I think Weka is not prepared to handle a large number of users.""Within the basic Weka tool, I don't see many tools that are available where we can analyze and visualize the data that well."

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Pricing and Cost Advice
  • "Having in mind all four tools from Garner’s top quadrant, the pricing of this tool is competitive and it reflects the quality that it offers."
  • "If you are in a university and the license is free then you can use the tool without any charges, which is good."
  • "It is a huge increase to time savings."
  • "The scalability was kind of limited by our ability to get other people licenses, and that was usually more of a financial constraint. It's expensive, but it's a good tool."
  • "When you are close to end of quarter, IBM and its partners can get you 60% to 70% discounts, so literally wait for the last day of the quarter for the best prices. You may feel like you are getting robbed if you can't receive a good discount."
  • "It got us a good amount of money with quick and efficient modeling."
  • "$5,000 annually."
  • "This tool, being an IBM product, is pretty expensive."
  • More IBM SPSS Modeler Pricing and Cost Advice →

  • "Currently, I am using an open-source version so I don't know much about the price of this solution."
  • "The solution is free and open-source."
  • "As far as I know, Weka is a freeware tool, and I am not aware if they have an online solution or if it is a commercial product."
  • "We use the free version now. My faculty is very small."
  • More Weka Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:Compared to other tools, the product works much easier to analyze data without coding.
    Top Answer:The platform's cloud version needs improvements. The process to access workflow could be user-friendly. It could be easier to log in and manage security levels. Additionally, it needs to be more… more »
    Top Answer:Weka is free and open-source software. That is why I used it over KNIME.
    Top Answer:I haven't found it particularly useful. It lacks state-of-the-art algorithms and impressive outcomes. While it might offer insights for basic warehouse tasks, it falls short of deeper understanding… more »
    Ranking
    4th
    out of 18 in Data Mining
    Views
    1,782
    Comparisons
    1,420
    Reviews
    6
    Average Words per Review
    372
    Rating
    7.3
    2nd
    out of 18 in Data Mining
    Views
    3,732
    Comparisons
    1,766
    Reviews
    7
    Average Words per Review
    518
    Rating
    7.9
    Comparisons
    Also Known As
    SPSS Modeler
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    IBM
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    Weka
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    Overview

    IBM SPSS Modeler is an extensive predictive analytics platform that is designed to bring predictive intelligence to decisions made by individuals, groups, systems and the enterprise. By providing a range of advanced algorithms and techniques that include text analytics, entity analytics, decision management and optimization, SPSS Modeler can help you consistently make the right decisions from the desktop or within operational systems.

    Buy
    https://www.ibm.com/products/spss-modeler/pricing
     
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    https://www.ibm.com/account/reg/us-en/signup?formid=urx-19947


    Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
    Sample Customers
    Reisebªro Idealtours GmbH, MedeAnalytics, Afni, Israel Electric Corporation, Nedbank Ltd., DigitalGlobe, Vodafone Hungary, Aegon Hungary, Bureau Veritas, Brammer Group, Florida Department of Juvenile Justice, InSites Consulting, Fortis Turkey
    Information Not Available
    Top Industries
    REVIEWERS
    University23%
    Financial Services Firm17%
    Manufacturing Company14%
    Government9%
    VISITORS READING REVIEWS
    Educational Organization16%
    Financial Services Firm10%
    Computer Software Company9%
    University8%
    VISITORS READING REVIEWS
    University18%
    Educational Organization14%
    Computer Software Company10%
    Comms Service Provider7%
    Company Size
    REVIEWERS
    Small Business19%
    Midsize Enterprise10%
    Large Enterprise71%
    VISITORS READING REVIEWS
    Small Business23%
    Midsize Enterprise13%
    Large Enterprise64%
    REVIEWERS
    Small Business70%
    Midsize Enterprise10%
    Large Enterprise20%
    VISITORS READING REVIEWS
    Small Business19%
    Midsize Enterprise18%
    Large Enterprise63%
    Buyer's Guide
    IBM SPSS Modeler vs. Weka
    March 2024
    Find out what your peers are saying about IBM SPSS Modeler vs. Weka and other solutions. Updated: March 2024.
    765,386 professionals have used our research since 2012.

    IBM SPSS Modeler is ranked 4th in Data Mining with 38 reviews while Weka is ranked 2nd in Data Mining with 14 reviews. IBM SPSS Modeler is rated 8.0, while Weka is rated 7.6. The top reviewer of IBM SPSS Modeler writes "Easy to use, quick to learn, and offers many ways to analyze data". 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 Modeler is most compared with KNIME, Microsoft Power BI, RapidMiner, IBM SPSS Statistics and IBM Watson Studio, whereas Weka is most compared with KNIME, IBM SPSS Statistics, Oracle Advanced Analytics, SAS Analytics and Splunk User Behavior Analytics. See our IBM SPSS Modeler vs. Weka report.

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