Results 231 to 240 of about 65,050 (262)

Dynamic Forest Model for Sentiment Classification

2017
Sentiment classification is a useful approach to analyse the emotional polarity of user reviews, and method based on machine learning has achieved a great success. In the era of Web2.0, the emotional intensity of terms will change with time and events, while a large number of Out-Of-Vocabulary (OOV) terms are appearing.
Mingming Li, Jiao Dai, Wei Liu, Jizhong Han   +3 more
openaire   +1 more source

Random forests based WCE frames classification

2012 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS), 2012
Wireless Capsule Endoscopy is a commonly used diagnostic technique to explore intestinal regions which are difficult to reach with traditional endoscopy. The large number of images produced by this technology requires the use of computer-aided tools to select only meaningful frames to speed up the analysis time by the expert.
GALLO, Giovanni, Torrisi A.
openaire   +1 more source

Classification Using Rough Random Forest

2015
The Rough random forest is a classification model based on rough set theory. The Rough random forest uses the concept of random forest and rough set theory in a single model. It combines a collection of decision trees for classification instead of depending on a single decision tree.
Rajhans Gondane, V. Susheela Devi
openaire   +1 more source

Random forests for land cover classification

IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477), 2004
In recent years, a number of works reported the use of combination of multiple classifiers to produce a single classification and demonstrated significant performance improvement. The resulting classifier, referred to as an ensemble classifier, is a set of classifiers whose individual decisions are combined by weighted or unweighted voting to classify ...
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Oxides Classification with Random Forests

2022
Kai Xiao, Baitong Chen, Wenzheng Bao, Honglin Cheng   +3 more
openaire   +1 more source

Classification Forests

2013
A. Criminisi, J. Shotton
openaire   +1 more source

An improved deep forest classification algorithm

International Journal of Modelling, Identification and Control, 2022
Jiaman Ding, Cuihua Liu, Runxin Li, Jinguo You, Lianyin Jia   +4 more
openaire   +1 more source

Experience of Forest Ecological Classification in Assessment of Vegetation Dynamics

Sustainability, 2022
Natalya Ivanova, V V Fomin, Antonin Kusbach   +2 more
exaly  

A comparison of random forest variable selection methods for classification prediction modeling

Expert Systems With Applications, 2019
Jaime Lynn Speiser, Janet A Tooze, Edward H Ip   +2 more
exaly  

An assessment of the effectiveness of a random forest classifier for land-cover classification

ISPRS Journal of Photogrammetry and Remote Sensing, 2012
VÍCTOR Rodríguez-Galiano, J Rogan, M Chica-Olmo   +2 more
exaly