Domain Knowledge Feature Engineering
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Feature engineering is fundamental to the application of machine learning and is both difficult and expensive.
Domain knowledge feature engineering. Having a good understanding of the problem statement clarity of the end objective and knowledge of the available data is essential to engineer domain specific features for the model. These features can be used to improve the performance of machine learning algorithms. I am not an it expert so i asked for help from my friend kamal and he told me that somebody who understands the business domain is called as domain expert.
Domain specific features this is the essence of feature engineering. Understanding of business model how money is made. Feature engineering is the process of using domain knowledge of the data to create features that make machine learning algorithms work.
Infuse domain knowledge you can often engineer informative features by tapping into your or others expertise about the domain. Unsurprisingly it can be easy to get stuck because feature engineering is so open ended. Here you have a lot of creative freedom.
Try to think of specific information you might want to isolate. Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. The code for manual feature engineering is problem dependent and must be re written for each new dataset.
These features can be used to improve the performance of machine learning algorithms. Data science central feature engineering is the process of using domain knowledge of the data to create features that make machine learning algorithms work. The traditional approach to feature engineering is to build features one at a time using domain knowledge a tedious time consuming and error prone process known as manual feature engineering.
Through feature engineering you can isolate key information highlight patterns and bring in domain expertise. In this guide we ll discuss 20 best practices and heuristics that will help you navigate feature engineering. Feature engineering can be considered as applied machine learning itself.
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