Maintenance planning of trucks at Scania have previously been done using static cyclic
plans with fixed sets of maintenance tasks, determined by mileage, calendar time, and some …

Predicting NOx sensor failure in heavy duty trucks using histogram-based random forests
Page 1 Predicting NOx sensor failure in heavy duty trucks using histogram-based random …

The standard approach of learning decision trees from histogram data is to treat the bins as
independent variables. However, as the underlying dependencies among the bins might not …

Machine learning algorithms for data containing histogram variables have not been
explored to any major extent. In this paper, an adapted version of the random forest …

Data mining and machine learning algorithms are trained on large datasets to find useful
hidden patterns. These patterns can help to gain new insights and make accurate …

A histogram-valued random variable represents its value by a list of pairs of bins and their
corresponding probabilities or relative frequencies. This type of data is a part of the symbolic …

Abstract‎ A histogram-valued observation is a specific type of symbolic objects that
represents its value by a list of bins (intervals) along with their corresponding relative …

A large volume of data has become commonplace in many domains these days. Machine
learning algorithms can be trained to look for any useful hidden patterns in such data …