Question

You are working on a time series data set. You manager has asked you to build a high accuracy model. You start with the decision tree algorithm, since you know it works fairly well on all kinds of data. Later, you tried a time series regression model and got higher accuracy than decision tree model. Can this happen? Why?

Answer 1

Yes, it is possible to get higher accuracy with a time series regression model compared to a decision tree model when working on a time series data set.

Step-by-step explanation:

Yes, it is possible to get higher accuracy with a time series regression model compared to a decision tree model when working on a time series data set. While decision tree algorithms work well on various types of data, they may not be the most suitable for time series data, which has a temporal aspect. Time series regression models, on the other hand, are specifically designed to handle time-dependent data and can capture the patterns and trends over time more accurately, resulting in higher accuracy.