#MissingData

[cizotech]

Is your AI driving blind? 🚗💨 Missing data = bad guesses = bad results!

Fix it with: ✅ Smart data filling ✅ Careful removal ✅ AI-powered gap-filling

Clean data = smarter AI! Ready to optimize? 👉 https://cizotech.com

Is Your AI Driving Blind?

Imagine giving your GPS half a map. You'd probably end up in a lake, right?

That's exactly what missing data does to your AI. It's like baking a cake without the sugar – the results are going to be…interesting. 😬

Missing data forces your AI to guess, and bad guesses lead to bad outcomes.

But don't worry, we've got a few tricks up our sleeves to fix this:

Fix #1: Filling in the Blanks We use clever techniques like averages or predictions to complete the missing pieces, making the data whole again.

Fix #2: Tossing Out the Junk (Carefully!) Sometimes, too much data is missing. In those cases, we might skip that part altogether, but we're always careful not to throw away anything important!

Fix #3: Advanced Models to the Rescue We leverage powerful models like TensorFlow to intelligently fill in the gaps. It's way better than just guessing.

Missing values can definitely wreak havoc on your AI, but with the right approach, you can turn things around and get your AI performing at its best.

𝐑𝐞𝐚𝐝𝐲 𝐭𝐨 𝐜𝐥𝐞𝐚𝐧 𝐮𝐩 𝐭𝐡𝐚𝐭 𝐝𝐚𝐭𝐚 𝐚𝐧𝐝 𝐦𝐚𝐤𝐞 𝐲𝐨𝐮𝐫 𝐀𝐈 𝐬𝐡𝐢𝐧𝐞? - Contact CIZO

[ihirinfotech]

If you don’t know, appending means to add to something. Therefore, data appending means to add to data.

In a business environment, it’s imperative to know just about everything about your customers. From what they bought, so when they bought it, to what time they bought it—every single piece of information is crucial to effectively market your brand.

In this article, I'm going briefly to explain How do Business Benefits from Data Appending?

[dethany-d]

DATA DIVE

5/29: In case you're wondering, yes, sunscreen is a must. https://comicskingdom.com/on-the-fastrack/2022-05-29

[addison1234]

If you export data with one of linkedin data extractor softwares anyway something important is missing in that data like email or phone number. In that case, you can utilize Linkedin Missing Data Scraper. This tool will take the extracted data record as info and scrape missing data like email and phone number from search engines and organization websites.

[mathnerd21-blog]

Classification Tree Analysis - Assignment #1

For this assignment, I used the gapminder data set provided by the course.  Per the course materials, “Gapminder contains data for all 192 UN members, aggregating data for Serbia and Montenegro.” (Course Materials).  For my model, I used all the predictor variables in the dataset with the exception of polityscore in order to predict the likelihood that a person lives to be greater than or equal to 70 years old.

In order to do this, i created a variable called “life” based on life expectancy.  If the life expectancy of a nation was >=70 then the value was set to 1, otherwise 0.  

My resulting tree is as follows:

Tracing the subtree leads to some interesting conclusions.  High income is correlated with a longer life expectancy.  Also, breast cancer rates below 38.892 per 100k and an hivrate < 2.386 correlate to a longer life expectancy.  

Looking at the terminal nodes, we see some interesting output.  For nations with income < $1154, a life expectancy of < 70 occurs at a 96% likelihood.  For those with an income above $1154, but a high breast cancer rate life expectancy of >=70 occurs 96% of the time.  Lastly, an hivrate >= 2.386 results in 100% likelihood of a life expectancy < 70 years, however, n=7 under this criteria. 

From this output, we see that income per person, breast cancer rates per 100k and employment rate are the biggest contributors to predicting life expectancy > 70 years..  

Our confusion matrix shows that our model does a pretty good job of predicting life expectancy.  Our ROC curve with an AUC of .96 would indicate that this is a “good” model.  

I grew the tree using Entropy and pruned the tree using COSTCOMPLEXITY.  This dataset also contains missing data, so I used MISSINGDATA=POPULAR.  The code is presented below:

LIBNAME mydata "/courses/d1406ae5ba27fe300 " access=readonly;

DATA work.gapminder; 

set mydata.gapminder;

if lifeexpectancy >=70 then life=1;

else life = 0;

run;

ods graphics on;

proc hpsplit seed=2004 ASSIGNMISSING=POPULAR;

class life;

model life =incomeperperson alcconsumption armedforcesrate breastcancerper100TH co2emissions

femaleemployrate employrate HIVrate Internetuserate oilperperson relectricperperson suicideper100TH urbanrate;

grow entropy;

prune costcomplexity;

RUN;

[bakakitsune-blog1]

Class projects suck!!!

So a whole column of data from a class project hasn’t been added to the table of results which I have to statistically analyse for 50% of my grade. Its not even something small, its one of the most important parts of the study! I’m so mad right now because I don’t want to fail because some asshole didn’t add their data!