Now showing items 1-4 of 4
Supervised non-parametric discretization based on Kernel density estimation
Nowadays, machine learning algorithms can be found in many applications where the classifiers play a key role. In this context, discretizing continuous attributes is a common step previous to classification tasks, the main ...
Approaching the Quadratic Assignment Problem with Kernels of Mallows Models under the Hamming Distance
The Quadratic Assignment Problem (QAP) is a specially challenging permutation-based np-hard combinatorial optimization problem, since instances of size $n>40$ are seldom solved using exact methods. In this sense, many ...
On-line Elastic Similarity Measures for time series
The way similarity is measured among time series is of paramount importance in many data mining and machine learning tasks. For instance, Elastic Similarity Measures are widely used to determine whether two time series are ...
On the evaluation and selection of classifier learning algorithms with crowdsourced data
In many current problems, the actual class of the instances, the ground truth, is unavail- able. Instead, with the intention of learning a model, the labels can be crowdsourced by harvesting them from different annotators. ...