Video classification is an essential step towards video perceptive. In recent years, the concept of utilizing association rules for classification emerged. This approach is more efficient and accurate than traditional techniques. Associative classifier integrates two data mining tasks such as association rule discovery and classification, to build a classifier for the purpose of prediction. The...

The definition of good classification rules for rule-based interpretation of remotely sensed data is a laborious and demanding task. One interesting method that could be used to automate the process is the classification tree method. It can be used to create a tree-structured classification hierarchy and rules automatically from training data. In this study, tests were carried out using the cla...

Individual tree species identification is important for urban forest inventory and ecology management. Recent advances in remote sensing technologies facilitate more detailed estimation of individual urban tree characteristics. This study presents an approach to improve the classification of individual tree species via longitudinal profiles from very high spatial resolution airborne imagery. Th...

Proteins were classified into their families using a classification tree method which is based on the coefficient of variations of physico-chemical and geometrical properties of the secondary structures of proteins. The tree method uses as splitting criterion the increase in purity when a node is split into two subnodes and the size of the tree is controlled by a threshold level for the improve...

In HRM, among the challenges for HR professionals is to manage an organization’s talents, especially to ensure the right person for the right job at the right time. Human talent prediction is an alternative to handle this issue. Due to that reason, classification and prediction in data mining which is commonly used in many areas can also be implemented to human talent. There are many classifica...

Mobile Laser Scanning data were collected simultaneously with hyperspectral data using the Finnish Geodetic Institute Sensei system. The data were tested for tree species classification. The test area was an urban garden in the City of Espoo, Finland. Point clouds representing 168 individual tree specimens of 23 tree species were determined manually. The classification of the trees was done usi...

The students’ performance monitoring and evaluation is an essential activity of an education system to keep track of the success and failure records of the students. The objective of this research is to provide the best classification model to predict the students’ academic performance. In this paper we propose a Multilevel Classification Model (MLCM) based on Decision Tree Algorithm for the pr...

BACKGROUND Gene expression data classification is a challenging task due to the large dimensionality and very small number of samples. Decision tree is one of the popular machine learning approaches to address such classification problems. However, the existing decision tree algorithms use a single gene feature at each node to split the data into its child nodes and hence might suffer from poor...