Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    data mining to find the right poly bag makers
    Using Data Analytics to Choose the Best Poly Mailer Bags
    12 Min Read
    data analytics for pharmacy trends
    How Data Analytics Is Tracking Trends in the Pharmacy Industry
    5 Min Read
    car expense data analytics
    Data Analytics for Smarter Vehicle Expense Management
    10 Min Read
    image fx (60)
    Data Analytics Driving the Modern E-commerce Warehouse
    13 Min Read
    big data analytics in transporation
    Turning Data Into Decisions: How Analytics Improves Transportation Strategy
    3 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: My PMML KXEN exported model has problems, how do I fix it?
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Uncategorized > My PMML KXEN exported model has problems, how do I fix it?
Uncategorized

My PMML KXEN exported model has problems, how do I fix it?

MichaelZeller
MichaelZeller
3 Min Read
SHARE

The latest KXEN software exports perfect PMML, however if you are using older versions of KXEN, the PMML model it exports may have some problems which will be picked-up by the PMML Converter during conversion or ADAPA during model upload. These hic-ups can be easily fixed. Here is a list of issues we encountered (and remedies we suggest).

1) Your PMML model needs to contain the URL with the address of the PMML schema. Our PMML Converter will add that to the model automatically once you pass it through the converter.

2) Models may contain DerivedFields for which optype = “continuous” but dataType = “string”. Just change the dataType to “double”.

3) Models may contain DerivedFields in which the output of a NormContinuous transformation is a float (dataType = “float”). Change the dataType to “double”.

More Read

Predicting popular stories on Digg
Ralph Vince 2009 Leverage Space …
Common Change
Economist Research: Decision-Making in Turbulent Times
Socially Speaking

4) For clustering models, make sure compareFunction = “absdiff” is expressed with a small “d”. Models may refer to “absDiff” instead which is not valid.

5) Again, for clustering models only, delete the element CenterFields (this is not valid PMML).

6) If you have a Mining Model, also check our blog on how to upload KXEN Mining Models into ADAPA.

Your model should be perfect now and ready for …


The latest KXEN software exports perfect PMML, however if you are using older versions of KXEN, the PMML model it exports may have some problems which will be picked-up by the PMML Converter during conversion or ADAPA during model upload. These hic-ups can be easily fixed. Here is a list of issues we encountered (and remedies we suggest).

1) Your PMML model needs to contain the URL with the address of the PMML schema. Our PMML Converter will add that to the model automatically once you pass it through the converter.

2) Models may contain DerivedFields for which optype = “continuous” but dataType = “string”. Just change the dataType to “double”.

3) Models may contain DerivedFields in which the output of a NormContinuous transformation is a float (dataType = “float”). Change the dataType to “double”.

4) For clustering models, make sure compareFunction = “absdiff” is expressed with a small “d”. Models may refer to “absDiff” instead which is not valid.

5) Again, for clustering models only, delete the element CenterFields (this is not valid PMML).

6) If you have a Mining Model, also check our blog on how to upload KXEN Mining Models into ADAPA.

Your model should be perfect now and ready for uploading into ADAPA.

Comprehensive blog featuring topics related to predictive analytics with an emphasis on open standards, Predictive Model Markup Language (PMML), cloud computing, as well as the deployment and integration of predictive models in any business process.

Link to original post

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

data mining to find the right poly bag makers
Using Data Analytics to Choose the Best Poly Mailer Bags
Analytics Big Data Exclusive
data science importance of flexibility
Why Flexibility Defines the Future of Data Science
Big Data Exclusive
payment methods
How Data Analytics Is Transforming eCommerce Payments
Business Intelligence
cybersecurity essentials
Cybersecurity Essentials For Customer-Facing Platforms
Exclusive Infographic IT Security

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Upstream Works Helps Customer Service Agents Improve Efficiency and Effectiveness

7 Min Read

Gamification Must Drive Software Ergonomics

6 Min Read

The Real Twitter

5 Min Read

Because it’s Friday: Carl Sagan sings the blueshift

1 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data
ai chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?