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Ordinal regression methods: survey and experimental study
(2017-02-03)
Abstract—Ordinal regression problems are those machine learning problems where the objective is to classify patterns using a
categorical scale which shows a natural order between the labels. Many real-world applications ...
Selecting patterns and features for between- and within- crop-row weed mapping using UAV-imagery
(2017-03-30)
This paper approaches the problem of weed mapping for precision agriculture,
using imagery provided by Unmanned Aerial Vehicles (UAVs) from sun
ower
and maize crops. Precision agriculture referred to weed control is ...
Borderline kernel based over-sampling
(2017-03-30)
Nowadays, the imbalanced nature of some real-world data
is receiving a lot of attention from the pattern recognition and machine
learning communities in both theoretical and practical aspects, giving
rise to di erent ...
Detection of early warning signals in paleoclimate data using a genetic time series segmentation algorithm
(2017)
This paper proposes a time series segmentation algorithm combining a clustering technique and a genetic algorithm to automatically find segments sharing common statistical characteristics in paleoclimate time series. The ...