Quantile regression refers to the process of estimating the quantiles of a conditional distribution and has many important applications within econometrics and data mining, among ...
Novi Quadrianto, Kristian Kersting, Mark D. Reid, ...
Random forests were introduced as a machine learning tool in Breiman (2001) and have since proven to be very popular and powerful for high-dimensional regression and classificatio...
In this paper we discuss the important practical problem of customer wallet estimation, i.e., estimation of potential spending by customers (rather than their expected spending). ...
Claudia Perlich, Saharon Rosset, Richard D. Lawren...
This paper examines a weighted version of the quantile regression estimator defined by Koenker and Bassett (1978), adjusted to the case of nonlinear longitudinal data. Different w...