IBM Smart Analytics vs Weka

IBM Smart Analytics is ranked 9th in Data Mining with 1 review vs Weka which is ranked 6th in Data Mining. The top reviewer of IBM Smart Analytics writes "Adding LA on top of a well deployed & working Tivoli Framework opens up a flood of native logged data points. The visual presentation layer of LA is less than cutting edge". IBM Smart Analytics is most compared with SAS Analytics, Oracle Advanced Analytics and IBM SPSS Statistics. Weka is most compared with KNIME, IBM SPSS Modeler and SAS Analytics.
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Most Helpful Review
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Quotes From Members Comparing IBM Smart Analytics vs Weka

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
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Ranking
RANKING
Views
783
Comparisons
184
Reviews
1
Followers
238
Avg. Rating
7.0
Views
4,854
Comparisons
3,892
Reviews
0
Followers
361
Avg. Rating
N/A
Top Comparisons
Top Comparisons
Sas
Compared 20% of the time.
See more IBM Smart Analytics competitors »
Uimhresp 400x400
Compared 59% of the time.
Ibm
Compared 17% of the time.
Sas
Compared 10% of the time.
See more Weka competitors »
Also Known As
Also Known AsSmart Analytics
Website/Video
Website/VideoIBM
  • Vendor 7400 screenshot 1524637054
Weka
  • Vendor 29286 screenshot 1524956374
OverviewQuestionmark icon
Overview
Information Not Available
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.
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Learn more about IBM Smart Analytics
Learn more about Weka
Sample Customers
Sample CustomersWIdO AOK, EEKA Fashion, SSGC, GS Retail
Information Not Available
Data mining report from it central station 2018 05 12 thumbnail
Find out what your peers are saying about IBM, Knime, SAS and others in Data Mining.
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270,047 professionals have used our research since 2012.
We monitor all Data Mining reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.

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