Two-stage hybrid feature selection algorithms for diagnosing erythemato-squamous diseases

This paper proposes two-stage hybrid feature selection algorithms to build the stable and efficient diagnostic models where a new accuracy measure is introduced to assess the models. The two-stage hybrid algorithms adopt Support Vector Machines (SVM) as a classification tool, and the extended Sequential Forward Search (SFS), Sequential Forward Floating Search (SFFS), and Sequential Backward Floating Search (SBFS), respectively, as search strategies, and the generalized F-score (GF) to evaluate the importance of each feature. The new accuracy measure is used as the criterion to evaluated the performance of a temporary SVM to direct the feature selection algorithms. These hybrid methods combine the advantages of filters and wrappers to select the optimal feature subset from the original feature set to build the stable and efficient classifiers. To get the stable, statistical and optimal classifiers, we conduct 10-fold cross validation experiments in the first stage; then we merge the 10 selected feature subsets of the 10-cross validation experiments, respectively, as the new full feature set to do feature selection in the second stage for each algorithm. We repeat the each hybrid feature selection algorithm in the second stage on the one fold that has got the best result in the first stage. Experimental results show that our proposed two-stage hybrid feature selection algorithms can construct efficient diagnostic models which have got better accuracy than that built by the corresponding hybrid feature selection algorithms without the second stage feature selection procedures. Furthermore our methods have got better classification accuracy when compared with the available algorithms for diagnosing erythemato-squamous diseases

A Tale of Three Galaxies: Anomalous Dust Properties in IRASF10398+1455, IRASF21013-0739 and SDSSJ0808+3948

On a galactic scale the 9.7um silicate emission is usually only seen in type 1 active galactic nuclei (AGNs). They usually also display a flat emission continuum at ~5--8um and the absence of polycyclic aromatic hydrocarbon (PAH) emission bands. In contrast, starburst galaxies, luminous infrared (IR) galaxies (LIRGs), and ultraluminous IR galaxies (ULIRGs) exhibit a red 5--8um emission continuum, strong 10um and 18um silicate absorption features, and strong PAH emission bands. Here we report the detection of anomalous dust properties by Spitzer/Infrared Spectrograph in three galaxies (IRASF10398+1455, IRASF21013-0739 and SDSSJ0808+3948) which are characterized by the simultaneous detection of a red 5--8um emission continuum, the 9.7 and 18um silicate emission features as well as strong PAH emission bands. These apparently contradictory dust IR emission properties are discussed in terms of iron-poor silicate composition, carbon dust deficit, small grain size and low dust temperature in the young AGN phase of these three galaxies.Comment: accepted for publication in ApJ