scholarly journals The Classification of Cropping Patterns Based on Regional Climate Classification Using Decision Tree Approach

2017 ◽  
Vol 13 (9) ◽  
pp. 408-415
Author(s):  
Tb Ai Munandar ◽  
Sumiati
Keyword(s):  
Decision Tree ◽  
Regional Climate ◽  
Climate Classification ◽  
Cropping Patterns ◽  
Tree Approach

A Successive Decision Tree Approach to Mining Remotely Sensed Image Data

2008 ◽  
pp. 2978-2992
Author(s):  
Jianting Zhang ◽  
Wieguo Liu ◽  
Le Gruenwald
Keyword(s):  
Decision Tree ◽  
Decision Trees ◽  
Classification Accuracy ◽  
Decision Rules ◽  
Image Data ◽  
Remotely Sensed ◽  
Fast Speed ◽  
Remotely Sensed Image ◽  
Tree Approach

Decision trees (DT) has been widely used for training and classification of remotely sensed image data due to its capability to generate human interpretable decision rules and its relatively fast speed in training and classification. This chapter proposes a successive decision tree (SDT) approach where the samples in the ill-classified branches of a previous resulting decision tree are used to construct a successive decision tree. The decision trees are chained together through pointers and used for classification. SDT aims at constructing more interpretable decision trees while attempting to improve classification accuracies. The proposed approach is applied to two real remotely sensed image datasets for evaluations in terms of classification accuracy and interpretability of the resulting decision rules.

scholarly journals IC-P1-051: Automatic diagnostic classification of dementia with FDG-PET using a spatial - decision tree approach

2008 ◽  
Vol 4 ◽  
pp. T28-T28
Author(s):  
N. Sadeghi ◽  
N.L. Foster ◽  
A.Y. Wang ◽  
S. Minoshima ◽  
A.P. Lieberman ◽  
...  
Keyword(s):  
Decision Tree ◽  
Fdg Pet ◽  
Diagnostic Classification ◽  
Tree Approach

A Successive Decision Tree Approach to Mining Remotely Sensed Image Data

2011 ◽  
pp. 98-112
Author(s):  
Jianting Zhang ◽  
Wieguo Liu ◽  
Le Gruenwald
Keyword(s):  
Decision Tree ◽  
Decision Trees ◽  
Classification Accuracy ◽  
Decision Rules ◽  
Image Data ◽  
Remotely Sensed ◽  
Fast Speed ◽  
Remotely Sensed Image ◽  
Tree Approach

Decision trees (DT) has been widely used for training and classification of remotely sensed image data due to its capability to generate human interpretable decision rules and its relatively fast speed in training and classification. This chapter proposes a successive decision tree (SDT) approach where the samples in the ill-classified branches of a previous resulting decision tree are used to construct a successive decision tree. The decision trees are chained together through pointers and used for classification. SDT aims at constructing more interpretable decision trees while attempting to improve classification accuracies. The proposed approach is applied to two real remotely sensed image datasets for evaluations in terms of classification accuracy and interpretability of the resulting decision rules.

scholarly journals P2-068: Automatic diagnostic classification of dementia with FDG-PET using a spatial decision tree approach

2008 ◽  
Vol 4 ◽  
pp. T387-T387
Author(s):  
N. Sadeghi ◽  
N.L. Foster ◽  
A.Y. Wang ◽  
S. Minoshima ◽  
A.P. Lieberman ◽  
...  
Keyword(s):  
Decision Tree ◽  
Fdg Pet ◽  
Diagnostic Classification ◽  
Tree Approach

Classification of nicotine-dependent users in India: a decision-tree approach

2018 ◽  
Vol 27 (4) ◽  
pp. 453-459
Author(s):  
Akansha Singh ◽  
Himanshu Katyan
Keyword(s):  
Decision Tree ◽  
Tree Approach
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