Background: A routine goal in the analysis of microarray data is to identify genes with expression levels that correlate with known classes of experiments. In a growing number of ...
We present a unifying framework for information theoretic feature selection, bringing almost two decades of research on heuristic filter criteria under a single theoretical inter...
Gavin Brown, Adam Pocock, Ming-Jie Zhao, Mikel Luj...
Perhaps the most common question that a microarray study can ask is, “Between two given biological conditions, which genes exhibit changed expression levels?” Existing methods...
Will Sheffler, Eli Upfal, John Sedivy, William Sta...
Obtaining high-quality and up-to-date labeled data can be difficult in many real-world machine learning applications, especially for Internet classification tasks like review spam...
Density-based clustering algorithms have recently gained popularity in the data mining field due to their ability to discover arbitrary shaped clusters while preserving spatial pr...
M. Emre Celebi, Y. Alp Aslandogan, Paul R. Bergstr...