Wednesday, February 24, 2021
  • Setup menu at Appearance » Menus and assign menu to Top Bar Navigation
Advertisement
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News
No Result
View All Result
NikolaNews
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News
No Result
View All Result
NikolaNews
No Result
View All Result
Home Neural Networks

How to date pretty people if you are ugly (using maths)

October 12, 2019
in Neural Networks
How to date pretty people if you are ugly (using maths)
586
SHARES
3.3k
VIEWS
Share on FacebookShare on Twitter

I know the feeling of a woman not giving value to your abilities with maths. You are intelligent, funny and honest, but that cute blonde girl that you like seems not to care about that. She keeps dating gym boys which, at the end, break her heart. This human behavior is called assortative mating, and it says that people tend to date with people who have similar physical traits, such as skin color or weight.

Lucky you, maths are going to help you with that (small) problem. I have to be honest: I love the title of this post. I know, it sounds like total clickbait, but it’s not!

You might also like

Statistical Concepts behind A/B Testing | by Sarvagya Dasgupta | Feb, 2021

Generating Music Using LSTM Neural Network | by Linan Chen | Jan, 2021

Convolutional Neural Networks with Keras | by Krishnakumar Karancherry

In this short but insightful text, I will review the paper called “Longer Acquaintance Predicts Reduced Assortative Mating on Attractiveness”, by Hunt et al. In their paper, the authors perform a study about the correlation between the difference in the beauty of the members of a couple and try to correlate it with other objective and measurable data.

Measuring couples beauty

The first step to correlate beauty with any other factor is, of course, to measure beauty. However, it may be difficult, as it’s an abstract feature which depends on the evaluator.

In the study of the paper, a total of 167 couples were assessed by different raters which gave independent punctuation to each member of the couple, ranging from -3 to +3. In order not to introduce a bias, the raters didn’t know anything about that person’s couple.

For a certain rater, we could plot the rating of one member of the couple against the rating of the other as:

Notice that the left-most plot corresponds to a scenario where beautiful people only date beautiful people. On the other hand, the right-most plot corresponds to the opposite scenario, where beautiful people only date ugly people (like me).

However, these are the two limit scenarios. We are interested in measuring a correlation index between the partners, where a correlation equal to 1 means a perfect correlation between beauties (similar to the left-most scenario) and a correlation equal to -1 measure the opposite (similar to the right-most scenario). If beauty is a redundant factor (such as knowing maths), then the correlation should be 0.

We can make use of Pearson’s correlation coefficient for this purpose, which is defined as:

Notice that the x would correspond to the marks of the raters for partner 1, while y would correspond to partner 2. We obtain the mean rating for both partner 1 and partner 2 (x_bar and y_bar, respectively) to normalize possible gender rating decompensations.

We obtain a different Pearson correlation coefficient (r_i) for each couple i.

Beating assortative mating with… longer acquaintance

Now that we have our beauty correlation index (r_i) for each couple, we can correlate it with other objective and measurable factors.

We could, for example, try to correlate it with the difference between the wages of the partners. Another funny factor could be to measure the sexual satisfaction of the partner with a greater rating. However, I’m not so sure that those factors can be included in a serious paper… without offending anyone.

Either way, in the paper the only factor that seems to have a correlation with beauty decompensation is to know the partner before dating him/her. That’s it, you have to be in the friend zone before you can finally date that cute girl/boy you like.

From now on, every time that your popular friend laughs at you because you are in the friend zone, tell him that you are just following math rules.

Credits to Enric Monte, my professor of Machine Learning at the Polytechnic University of Catalonia, for his special class on this topic.

Credit: BecomingHuman By: David Álvarez de la Torre

Previous Post

Microsoft and NIST partner to create enterprise patching guide

Next Post

Google to Use Machine Learning to Manage Ad Frequency When Cookies Are Missing

Related Posts

Statistical Concepts behind A/B Testing | by Sarvagya Dasgupta | Feb, 2021
Neural Networks

Statistical Concepts behind A/B Testing | by Sarvagya Dasgupta | Feb, 2021

February 24, 2021
Generating Music Using LSTM Neural Network | by Linan Chen | Jan, 2021
Neural Networks

Generating Music Using LSTM Neural Network | by Linan Chen | Jan, 2021

February 24, 2021
Convolutional Neural Networks with Keras | by Krishnakumar Karancherry
Neural Networks

Convolutional Neural Networks with Keras | by Krishnakumar Karancherry

February 24, 2021
How I meet the KNN algorithm.. During the study of Data Science, I met… | by Mari Galdina | Feb, 2021
Neural Networks

How I meet the KNN algorithm.. During the study of Data Science, I met… | by Mari Galdina | Feb, 2021

February 23, 2021
No Bias Labeled Data — the New Bottleneck in Machine Learning | by ByteBridge | Feb, 2021
Neural Networks

No Bias Labeled Data — the New Bottleneck in Machine Learning | by ByteBridge | Feb, 2021

February 23, 2021
Next Post
Google to Use Machine Learning to Manage Ad Frequency When Cookies Are Missing

Google to Use Machine Learning to Manage Ad Frequency When Cookies Are Missing

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Recommended

Plasticity in Deep Learning: Dynamic Adaptations for AI Self-Driving Cars

Plasticity in Deep Learning: Dynamic Adaptations for AI Self-Driving Cars

January 6, 2019
Microsoft, Google Use Artificial Intelligence to Fight Hackers

Microsoft, Google Use Artificial Intelligence to Fight Hackers

January 6, 2019

Categories

  • Artificial Intelligence
  • Big Data
  • Blockchain
  • Crypto News
  • Data Science
  • Digital Marketing
  • Internet Privacy
  • Internet Security
  • Learn to Code
  • Machine Learning
  • Marketing Technology
  • Neural Networks
  • Technology Companies

Don't miss it

Bill establishing cyber abuse takedown scheme for adults enters Parliament
Internet Security

Bill establishing cyber abuse takedown scheme for adults enters Parliament

February 24, 2021
A Plethora of Machine Learning Articles: Part 1
Data Science

A Plethora of Machine Learning Articles: Part 1

February 24, 2021
Market Live: Global Machine Learning Big Data Analytics Education Market Can Deliver up to High CAGR over the next Few Years | COVID19 Impact Analysis
Machine Learning

Global Machine Learning Market 2021 Size, Industry Growth and Forecast till 2025 | COVID19 Impact Analysis

February 24, 2021
Statistical Concepts behind A/B Testing | by Sarvagya Dasgupta | Feb, 2021
Neural Networks

Statistical Concepts behind A/B Testing | by Sarvagya Dasgupta | Feb, 2021

February 24, 2021
6 Prerequisites for Responsive Brand Marketing
Marketing Technology

6 Prerequisites for Responsive Brand Marketing

February 24, 2021
McAfee shares jump on first public report: Q4 revenue tops expectations, outlook higher as well
Internet Security

McAfee shares jump on first public report: Q4 revenue tops expectations, outlook higher as well

February 24, 2021
NikolaNews

NikolaNews.com is an online News Portal which aims to share news about blockchain, AI, Big Data, and Data Privacy and more!

What’s New Here?

  • Bill establishing cyber abuse takedown scheme for adults enters Parliament February 24, 2021
  • A Plethora of Machine Learning Articles: Part 1 February 24, 2021
  • Global Machine Learning Market 2021 Size, Industry Growth and Forecast till 2025 | COVID19 Impact Analysis February 24, 2021
  • Statistical Concepts behind A/B Testing | by Sarvagya Dasgupta | Feb, 2021 February 24, 2021

Subscribe to get more!

© 2019 NikolaNews.com - Global Tech Updates

No Result
View All Result
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News

© 2019 NikolaNews.com - Global Tech Updates