Chapter 5. Regression on Big Data
Regression is a form of machine learning where we try to predict a continuous value based on some variables. It is a form of supervised learning where a model is taught using some features from existing data. From the existing data the regression model then builds its knowledge base. Based on this knowledge base the model can later make predictions for outcomes on new data.
Continuous values are numerical or quantitative values that have to be predicted and are not from an existing set of labels or categories. There are lots of examples of regression where it is heavily used on a daily basis and in many cases it has a direct business impact. Some of the use cases where regression can be used are the following:
- To estimate the price of a product based on some criteria or variables
- For demand forecasting, so you can predict the amount of sales of a product based on certain features such as amount spent on advertising, and so on
- To estimate the hit count...
