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Wish it shed more insight how it deemed one title better than the other. I tested with: Title A: Google pledging to spend 2 billion by 2022 to get rid of php o
by cghendrix 6y ago
Wish it shed more insight how it deemed one title better than the other.
I tested with:
Title A: Google pledging to spend 2 billion by 2022 to get rid of php on the web.
Title B: I stopped using php and here’s how it saved my marriage.
Title B won.
Note: nothing against php, just wanted to test some typical cringey, hyperbolic tech article titles I constantly see LOL.
- ihmissuti 6y agoThanks for testing! I'll write a description of how it makes the predictions and add it to the tool. But in short, it uses a machine learning model that I trained with a dataset that contains all stories and comments between 2006 and 2017: https://www.kaggle.com/hacker-news/hacker-news https://www.kaggle.com/hacker-news/hacker-news I've tested various approaches, and currently, the algorithm takes the title as an input and transforms it into an array of numbers between 0 and 1 (each character is a number). Then I give these arrays to the machine learning model (brain.js feed-forward neural network) and the number of scores as an output. After learning and iterating over the data, it spits out the prediction model that I can use to predict the outcome of different title variations. I've tested the algorithm with approx. 10.000 posts and it has been able to predict 60% of the cases correctly. So, it's not perfect yet, but I use this method in a situation where I don't have any experience of which type of title would work + I don't have time to do "proper" pre-testing.