Chapter 11
Predicting the Future with Regression
IN THIS CHAPTER
Capitalizing on trends
Identifying indicators of future activity
Choosing the right regression method for your data
Determining the accuracy of your model
Writing Python code to predict future outcomes
Chapter 10 presented a couple ways to predict the future with analytics. The techniques you learn in Chapter 10 work well for categorical outcomes, which are situations in which the outcome, or result, is one item from a list of options. For example, if your model attempts to predict the best day of the week to purchase an airline ticket, the outcome would be one of the seven days of the week. You could use a decision tree or naïve Bayes approach to build your model.
Sometimes your outcome might not fit into a clean list of options. Suppose your model attempts to predict tomorrow’s price for a specific stock. The answer could be any price. Data that represents values in a range is called continuous data. Analytics models ...
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