@paper{Chang2017,
	author = {Stephan Chang and Felipe Meneguzzi},
	title = {Forecasting demand with limited information using Gradient Tree Boosting},
	conference = {The 30th Florida Artificial Intelligence Research Society Conference},
	year = {2017},
	keywords = {Forecasting; Gradient Tree Boosting; Machine Learning},
	abstract = {Demand forecasting is an important challenge for industries seeking to optimize service quality and expenditures. Generating accurate forecasts is difficult because it depends on the quality of the data available to train predictive models, as well as on the model chosen for the task. We evaluate the approach on two datasets of varying complexity and compare the results with three machine learning algorithms, Results show our approach can outperform these approaches.},

	url = {http://www.meneguzzi.eu/felipe/pubs/flairs-demand-forecasting-2017.pdf}
}