An Empirical Study for PCA- and LDA-Based Feature Reduction for Gas Identification
Electronic Nose (EN) systems utilize commercial gas sensors for sensing and computer platforms for processing. An integrated gas sensor array, on the contrary, can increase the selectivity and detect multiple target gases with a single device. The central premise when using a feature selection technique is that the data contains many features that are either redundant or irrelevant, and can thus be removed without incurring much loss of information. Redundant or irrelevant features are two distinct notions, since one relevant feature may be redundant in the presence of another relevant feature with which it is strongly correlated. Feature selection techniques should be distinguished from feature extraction. Feature extraction creates new features from functions of the original features, whereas feature selection returns a subset of the features.
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