TV Ratings Prediction with Time Weighting Based Regression
Date Issued
2015
Date
2015
Author(s)
Ku, Ting-Wei
Abstract
In this thesis, the primary contribution is proposing a simple and experimentally accurate solution, named Time Weighting Regression (TWR), to the problem of TV ratings prediction. Based on the assumption that newer data are more important for predicting upcoming ratings, what TWR does is: weighing data based on time, and then using weighted data to build regression model for predicting upcoming ratings. In the experiments on a real-world TV ratings data set, it outperforms well-known time series models (e.g., Exponential Smoothing and ARIMA) and regression model (neural network).
Subjects
time series prediction
TV ratings prediction
regression
Type
thesis
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