I get how those methods can be useful for making models better. They can help spot tricky patterns and deal with unusual data points. But, since I’m not actually working in this area yet, my worry is about talking to the people who care about the results. When you tell them about your work, do you mention using these methods? Like, if you’re using a basic method like linear regression on a table of data.
You wouldn’t believe how common feature transformations are in the real world, especially those like ranking, square root, and logarithm! These aren’t just some abstract math concepts – they’re the secret sauce behind a ton of everyday things.
Let me give you some examples:
Recommendation Systems: When you browse online and see products recommended "just for you," that's often thanks to feature transformations. They take all sorts of data about you and the products (like your purchase history, product views, and ratings) and transform it in a way that helps recommend things you'll like. For instance, they might use a ranking transformation to prioritize items you looked at for a long time.
Image Search: Ever done a reverse image search to find similar pictures? Feature transformations are at play there too. They take the image data and convert it into a format that lets the search engine find similar pictures easily. Think of it like transforming a complicated painting into a simple code that the search engine can understand.
Weather Forecasting: Meteorologists use a ton of data to predict the weather, like temperature, humidity, and wind speed. However, these values aren't always directly useful for forecasting. That's where feature transformations come in. They might take the square root of the temperature to better understand how it affects things like precipitation, or use a log transformation to model how wind speed scales with its impact.
Social Media Trends: How do you think social media platforms track what's trending? They use feature transformations! They take all the likes, shares, and comments, and transform them into a format that shows what's gaining popularity the fastest. They might look at the rate of change in likes (like a steep increase is a hotter trend) or use a ranking system to show the most engaged content.
I personally use squareroot. Its commonly used
I use ranking in various fields and applications to convert data or variables from one form to another.
Logarithmic transformations are frequently used for variables like income, revenue, and GDP. These variables measure wealth or richness, and typically have fewer entries as their values increase.