2090 search results - page 18 / 418 » Learning with attribute costs |
MLDM
2005
Springer
14 years 1 months ago
2005
Springer
In supervised machine learning, the partitioning of the values (also called grouping) of a categorical attribute aims at constructing a new synthetic attribute which keeps the info...
AUSAI
2006
Springer
13 years 11 months ago
2006
Springer
Attribute subsetting is a meta-classification technique, based on learning multiple base-level classifiers on projections of the training data. In prior work with nearest-neighbour...
ICANN
2011
Springer
12 years 11 months ago
2011
Springer
Attribute importance measures for supervised learning are important for improving both learning accuracy and interpretability. However, it is well-known there could be bias when th...
HAPTICS
2009
IEEE
14 years 2 months ago
2009
IEEE
Human vibrotactile detection experiments were used to compare temporal sinusoids displayed on three commercial haptic devices to a high-fidelity linear voice-coil actuator. The t...
EPIA
2003
Springer
14 years 27 days ago
2003
Springer
This paper presents an incremental and scalable learning algorithm in order to mine numeric, low dimensionality, high–cardinality, time–changing data streams. Within the Superv...