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Machine learning algorithms are computer programs that try to predict cancer type based on the past data. The eventual goal of Machine learning algorithms in cancer diagnosis is to have a trained machine learning algorithm that gives the gene expression levels from cancer patient, can accurately predict what type and severity of cancer they have, aiding the doctor in treating it. The existing technology...
A diamond adsorption detecting system based on machine learning is presented in this paper. The paper describes the system from the perspective of hardware and software design, and presents the image processing and machine learning algorithms applied in the system. The hardware includes three major parts — the camera, light source and support platform. The software includes modules of image acquisition,...
Recovering design patterns applied in a system can help refactoring the system. Machine learning algorithms have been successfully applied in mining data patterns. However, one of the main obstacles of applying them for design pattern detection is the difficulty of collecting training examples. Unlike other applications, a design pattern instance typically includes a group of classes with certain...
The identification of network applications is of fundamental important to numerous network activities. Unfortunately, traditional port-based classification and packet payload-based analysis exhibit a number of shortfalls. A promising alternative is to use Machine Learning (ML) techniques and identify network applications based on per-flow features. Since a lot of flow features can be used for flow...
Existing classification methods which are based on the homogeneous-region mostly involve the best segmentation scale choice. Using the so-called best segmentation scale to respond the subjective defined objects, it would not be the best way for classification. Therefore we propose a simple classification method with high precision. It is a new kind of multi-scale homogeneous-region model, fully uses...
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