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 analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 Min Read
    predictive analytics for interior designers
    Interior Designers Boost Profits with Predictive Analytics
    8 Min Read
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
    big data and remote work
    Data Helps Speech-Language Pathologists Deliver Better Results
    6 Min Read
    data driven insights
    How Data-Driven Insights Are Addressing Gaps in Patient Communication and Equity
    8 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: More Ways to get a Scoring Model wrong
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Mining > More Ways to get a Scoring Model wrong
Data Mining

More Ways to get a Scoring Model wrong

Editor SDC
Editor SDC
5 Min Read
SHARE

I got the following answer from Linkedin groups**

 

on my Ten Ways to get a Scoring Model Wrong.

  1.  Typo 
  2. Refuse to use central tendency to patch missing values. Instead, assign highest response rate because WOE says so 
  3. Marketing people tell me to force the variable into the model 
  4.  Selection bias 
  5.  Forgot to segment 
  6. Solely rely on data to segment without consulting the biz side 
  7.  Just delete observations with missing values, OK, without studying geometricl boundaries 
  8.  Using oversampling, but refuse to weight it back. That boosts lift, right? Let us do 50-50 
  9. Insist random sampling is sufficient, while stratified sampling is critical 
  10. Binning too much, or two little 
  11. Selecting variables without repeated sampling 
  12. Forgot to exclude numeric customer id from the candidate variables. AND,it pops….Well, both Unica and Kxen accepted it, So I see no problem 
  13. When the same variable is sourced by different vendors, did not look up the scales under the same name. Just combine them 
  14.  Well, SAS Enterprise Miner gave me this mode…

More Read

Is Big Data at Risk of Unleashing Big Brother?
A Decision is a prerequisite for success with predictive analytics
Why you won’t be building your killer app on a distributed hash table
Decide.com – New Search Ideas for Unstructured Data
Dharmendra Modha describes IBM’s research in Whole Brain…

I got the following answer from Linkedin groups**

 

on my Ten Ways to get a Scoring Model Wrong.

  1.  Typo 
  2. Refuse to use central tendency to patch missing values. Instead, assign highest response rate because WOE says so 
  3. Marketing people tell me to force the variable into the model 
  4.  Selection bias 
  5.  Forgot to segment 
  6. Solely rely on data to segment without consulting the biz side 
  7.  Just delete observations with missing values, OK, without studying geometricl boundaries 
  8.  Using oversampling, but refuse to weight it back. That boosts lift, right? Let us do 50-50 
  9. Insist random sampling is sufficient, while stratified sampling is critical 
  10. Binning too much, or two little 
  11. Selecting variables without repeated sampling 
  12. Forgot to exclude numeric customer id from the candidate variables. AND,it pops….Well, both Unica and Kxen accepted it, So I see no problem 
  13. When the same variable is sourced by different vendors, did not look up the scales under the same name. Just combine them 
  14.  Well, SAS Enterprise Miner gave me this model yesterday 
  15. The binary variable is statistically significant, but there are only 27 event=1, out of ~1mm, since only 27 made some purchases.. 
  16. Well, I only have 250 events=1. But I think I can use exact logistic to make it up, all right? I got a PHD in Statistics, Trust me, my professor is OK with it. I just called her. 
  17.  Build two-stage model without Heckman adjustment 
  18. Use global mean over the WHOLE customer base to replace missing value on a much smaller universe/subset. So average networth of a high networth client group has 22% worth only 225K 
  19. I just spent the past two days boosting R-square. Now it is 92. Great. 
  20. Forgot to set descending option in proc logistic in SAS 
  21. I think we should hold out missing values when conducting EDA. 
  22. Without proper separation of ‘treatment and control 
  23. Treat business entities and individuals as equal and mix them in the same universe
  24. Runing clustering without validation 
  25. Running discriminant model without validation. So correct classification rate on development is 89% and that over validation is …35%.(no wonder you finished it in two hours and came here to ask me for a raise) 
  26. Disregard link function in multi-nomil models 
  27. I think this is a better variable: xnew=y*y*y*. It is the top variable dominating others. 
  28. Use standardized coefficient to calculate relative importance, because many people are doing and marketing loves it. 
  29. I tried Goolge Analtyics last Friday. It recommends this variable: click stream density over Thanksgivning weekend, on my web portal, on this item 
  30.  Let us treat this matrix as unary so we can apply Euclidean, since that runs faster and has a lot of optimal properties. It makes our life easier 
  31. Let us use score from that model to boost this model and use score from this model to boost it back. Is that what they call neural nets, Jia? 

Enough?

 

31 Ways to get a model wrong – and Hats off to a fellow mate in suffering -Jia**

 http://www.linkedin.com/groupAnswers?viewQuestionAndAnswers=&gid=53432&discussionID=1946379&commentID=2213879&goback=.mgr_false_0_DATE.mgr_true_1_DATE.mid_1066685320#commentID_2213879

Coming up – One Way to get a scoring model correct

Share/Save/Bookmark

TAGGED:modellingscoring models
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

data analytics and truck accident claims
How Data Analytics Reduces Truck Accidents and Speeds Up Claims
Analytics Big Data Exclusive
predictive analytics for interior designers
Interior Designers Boost Profits with Predictive Analytics
Analytics Exclusive Predictive Analytics
big data and cybercrime
Stopping Lateral Movement in a Data-Heavy, Edge-First World
Big Data Exclusive
AI and data mining
What the Rise of AI Web Scrapers Means for Data Teams
Artificial Intelligence Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Interview: Françoise Soulie Fogelman, KXEN

11 Min Read

Ten ways to build a wrong scoring model

3 Min Read

Physicists, models, and the credit crisis

3 Min Read

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

ai chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots
AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
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?