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Many cancer treatments destroy healthy cells along with cancerous ones, and can leave patients fatigued and with a compromised immune system. This makes it especially important to determine whether or not a given cancer treatment will work for the patient or will just cause further harm. Recently there has been work on using gene expression profiles (DNA microarrays) to predict how a patient will...
Ensemble gene (feature) selection is a promising new strategy with many benefits including more stable gene lists and improved classification results. The ensemble portion is achieved through multiple runs of feature selection which are then aggregated into a single result. The critical question is how many iterations of feature selection are appropriate. Too few iterations can make classification...
Dimensionality-reducing techniques such as gene selection have become commonplace in order to reduce the high dimensionality found within bioinformatics datasets such as DNA microarray datasets. The degree of dimensionality is reduced by identifying and removing redundant and irrelevant features or genes and leaving only an optimum subset of features for subsequent analysis. However, a number of feature...
In large software projects, software quality prediction is an important aspect of the development cycle to help focus quality assurance efforts on the modules most likely to contain faults. To perform software quality prediction, various software metrics are collected during the software development cycle, and models are built using these metrics. However, not all features (metrics) make the same...
Univariate feature rankers have been frequently used to order genes (features) in terms of their importance to a given bioinformatics challenge. Unfortunately, the resulting feature subsets tend to differ when applied to related (but distinct) datasets, or when applied to datasets which have been varied or corrupted in some fashion. As a result, a research focus has recently been on methods to measure...
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