We use cookies, including third-party cookies from Google to serve personalized ads through AdSense, to operate this site and understand how it is used. By continuing to browse, you accept this use. See our Privacy Policy and Terms of Use for details, including how to opt out of personalized advertising.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers -- AI-generated illustration
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers
    7 Min Read
    chatgpt image jul 21, 2026, 04 34 30 pm
    4 Core Benefits of Predictive Maintenance after Vibration Analysis
    10 Min Read
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results -- AI-generated illustration
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results
    11 Min Read
    chatgpt image jul 13, 2026, 04 23 45 pm
    How Data Analytics Helps Companies Improve User Engagement
    19 Min Read
    chatgpt image jul 13, 2026, 03 59 46 pm
    How Data Analytics Improves Multi-Location Search Strategies
    10 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: How does ADAPA handle missing values for Decision Trees?
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 > How does ADAPA handle missing values for Decision Trees?
Uncategorized

How does ADAPA handle missing values for Decision Trees?

MichaelZeller
MichaelZeller
1 Min Read
How does ADAPA handle missing values for Decision Trees?
Illustration generated with Qwen Image.
SHARE

PMML 3.2 offers many different strategies for the handling of missing values in Decision Trees. ADAPA supports all of them. These are:

  • lastPrediction
  • nullPrediction
  • defaultChild
  • weightedConfidence
  • aggregateNodes
  • none (default strategy)

For information on each strategy, please visit the PMML 3.2 Decision Trees specification page at the Data Mining Group website.

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.

More Read

What I've discovered about Twitter
What I’ve discovered about Twitter
eMail is Dead, Long Live Social Networking: Don’t Get Left Behind
Lambda Complexity: Why Fast Data Needs New Thinking
How HR Can Use Big Data in a Smart Way (Hint: Most Are Not)
The World According to IT: The Star Wars Spectrum of User Intelligence [INFOGRAPHIC]

Link to original post

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Flat editorial illustration: The article explains that training robots for physical interaction requires three distinct data cate
Physical AI: What Data Do You Need to Train a Robot?
Artificial Intelligence Exclusive Robotics
What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers -- AI-generated illustration
What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers
Analytics Big Data Exclusive Software
Flat editorial illustration: The article examines AI agents that escalate from legitimate data retrieval to attempted intrusions
OpenAI’s Government Website Incidents Raise a Hard Question for AI Agents: When Should They Stop?
Artificial Intelligence News Security
Flat editorial illustration: The article's core relationship is the alignment between customer behavioral data (visit frequency,
Data-Driven Loyalty: How Restaurants Use Behavioral Analytics to Optimize Revenue
Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

4 Retail BI Lessons to Learn from Google's Nexus Fail
Uncategorized

4 Retail BI Lessons to Learn from Google’s Nexus Fail

5 Min Read
Cruiser and PhoTable: Limited by your imagination
Uncategorized

Cruiser and PhoTable: Limited by your imagination

7 Min Read
What is DIG?
Uncategorized

What is DIG?

5 Min Read
It’s not East Coast vs West Coast, it’s about making more places like the Valley
Uncategorized

It’s not East Coast vs West Coast, it’s about making more places like the Valley

5 Min Read

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

5 Great Tips for Using Data Analytics for Website UX
5 Great Tips for Using Data Analytics for Website UX
Big Data
AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-26 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?