Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
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Data mining courses have become popular electives in many graduate and undergraduate computer science curriculums. In these courses we usually give a comprehensive coverage of data mining concepts, algorithms, methodologies, management issues, and tools, which are illustrated through simple examples for an easy understanding and mastering of these materials. However, these courses often fail to provide students with opportunities to develop and evaluate applications in real-world environments. We fill these gaps by creating new materials in cancer research which would open opportunities to develop and evaluate applications in real-world environments for the senior-level and graduate students in computer science. In this paper, we show how new data mining techniques can be developed and used to improve the classification of non-small cell lung carcinoma (NSCLC) cancer. The outcomes of this research are used as new materials for students in our data mining courses.