214 search results - page 4 / 43 » Semi-Supervised Random Forests |
NLPRS
2001
Springer
13 years 10 months ago
2001
Springer
Recent research in automated learning has focused on algorithms that learn from a combination of tagged and untagged data. Such algorithms can be referred to as semi-supervised in...
IJSI
2008
13 years 6 months ago
2008
Many data mining applications have a large amount of data but labeling data is often difficult, expensive, or time consuming, as it requires human experts for annotation. Semi-supe...
JMLR
2006
13 years 6 months ago
2006
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...
IDEAS
2007
IEEE
14 years 17 days ago
2007
IEEE
Many recent applications deal with data streams, conceptually endless sequences of data records, often arriving at high flow rates. Standard data-mining techniques typically assu...
CIVR
2008
Springer
13 years 8 months ago
2008
Springer
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...