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The pool-based active learning intends to collect the samples into the pool firstly, and selects the best informative sample from it which has no label to add into the training sets for updating the classifier secondly. This paper proposed a new method based on the incremental decision tree algorithm to measure the ambiguity of the unlabeled samples for the sample selection in the active learning.
In the field of image segmentation, because of the exist of the noise dot and misjudgment, hollows and the unexpected image are unavoidable. In order to get a high quality segmented image the process of connected component analysis is necessary. This paper proposed a new algorithm that used a kind of tree-structure named max-tree, the experiment shows this method has a high practical value.
Web public sentiment reflects the people's attitude to society and politics, it's important to identify the web sensitive information correctly to build a harmonious network. Those existing monitoring systems relied on large common category libraries to do accurate identification, yet faced with the new and unknown events which is not recorded in the category libraries did not do in-depth research...
Web document classification is the process of grouping web documents into one or more predefined categories based on their content. It is an important component of web monitor system that can assist people to reduce the dissemination of harmful information. This paper proposes a combined approach for building a decision tree with the multilayer neural network as its categorically value function, and...
To study effective speech features which can represent different emotion styles in infant voice, nonlinear features based on Teager Energy Operator are investigated. Neutral state and 4 emotional states (i.e. happiness, impatience, anger and fear) are classified from the infant voice database. MFCC extraction and HMM-based emotion classification are used as baseline system to evaluate the emotional...
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