Search results for "pattern"
showing 10 items of 4203 documents
GenClust: A genetic algorithm for clustering gene expression data
2005
Abstract Background Clustering is a key step in the analysis of gene expression data, and in fact, many classical clustering algorithms are used, or more innovative ones have been designed and validated for the task. Despite the widespread use of artificial intelligence techniques in bioinformatics and, more generally, data analysis, there are very few clustering algorithms based on the genetic paradigm, yet that paradigm has great potential in finding good heuristic solutions to a difficult optimization problem such as clustering. Results GenClust is a new genetic algorithm for clustering gene expression data. It has two key features: (a) a novel coding of the search space that is simple, …
Data Analysis and Bioinformatics
2007
Data analysis methods and techniques are revisited in the case of biological data sets. Particular emphasis is given to clustering and mining issues. Clustering is still a subject of active research in several fields such as statistics, pattern recognition, and machine learning. Data mining adds to clustering the complications of very large data-sets with many attributes of different types. And this is a typical situation in biology. Some cases studies are also described.
Structural clustering of millions of molecular graphs
2014
We propose an algorithm for clustering very large molecular graph databases according to scaffolds (i.e., large structural overlaps) that are common between cluster members. Our approach first partitions the original dataset into several smaller datasets using a greedy clustering approach named APreClus based on dynamic seed clustering. APreClus is an online and instance incremental clustering algorithm delaying the final cluster assignment of an instance until one of the so-called pending clusters the instance belongs to has reached significant size and is converted to a fixed cluster. Once a cluster is fixed, APreClus recalculates the cluster centers, which are used as representatives for…
Dimensionality reduction via regression on hyperspectral infrared sounding data
2014
This paper introduces a new method for dimensionality reduction via regression (DRR). The method generalizes Principal Component Analysis (PCA) in such a way that reduces the variance of the PCA scores. In order to do so, DRR relies on a deflationary process in which a non-linear regression reduces the redundancy between the PC scores. Unlike other nonlinear dimensionality reduction methods, DRR is easy to apply, it has out-of-sample extension, it is invertible, and the learned transformation is volume-preserving. These properties make the method useful for a wide range of applications, especially in very high dimensional data in general, and for hyperspectral image processing in particular…
The Three Steps of Clustering In The Post-Genomic Era
2013
This chapter descibes the basic algorithmic components that are involved in clustering, with particular attention to classification of microarray data.
A Feature Set Decomposition Method for the Construction of Multi-classifier Systems Trained with High-Dimensional Data
2013
Data mining for the discovery of novel, useful patterns, encounters obstacles when dealing with high-dimensional datasets, which have been documented as the "curse" of dimensionality. A strategy to deal with this issue is the decomposition of the input feature set to build a multi-classifier system. Standalone decomposition methods are rare and generally based on random selection. We propose a decomposition method which uses information theory tools to arrange input features into uncorrelated and relevant subsets. Experimental results show how this approach significantly outperforms three baseline decomposition methods, in terms of classification accuracy.
Beyond decomposition: Processing zero-derivations in English visual word recognition
2019
Four experiments investigate the effects of covert morphological complexity during visual word recognition. Zero-derivations occur in English in which a change of word class occurs without any change in surface form (e.g., a boat-to boat; to soak-a soak). Boat is object-derived and is a basic noun (N), whereas soak is action-derived and is a basic verb (V). As the suffix {-ing} is only attached to verbs, deriving boating from its base, requires two steps, boat(N) > boat(V) > boating(V), while soaking can be derived in one step from soak(V). Experiments 1 to 3 used masked priming at different prime durations to test matched sets of one- and two-step verbs for morphological (soaking-SOA…
A Formalism Supplementing Cognitive Semantics Based on Mereology
2007
ABSTRACT This paper is motivated by and aims to supplement Cognitive Semantics. Details of this latter prominent approach within contemporary linguistic research will not be discussed here. Rather, we focus on a formalization of the concept of Gestalt and provide a formal semantics that can be used to interpret a certain formal language (LM 0) with respect to a universe of structured wholes (Gestalts). Since a great deal of the analyses of linguistic organization that has been provided by Cognitive Semantics since the mid-1970s is based on the concept of Gestalt, the semantics unfolded in the following may be viewed as an attempt to provide a starting point for supplementing the yet informa…
A musical reading of a contemporary installation and back: mathematical investigations of patterns in Qwalala
2021
Mathematical music theory helps us investigate musical compositions in mathematical terms. Some hints can be extended towards the visual arts. Mathematical approaches can also help formalize a "translation" from the visual domain to the auditory one and vice versa. Thus, a visual artwork can be mathematically investigated, then translated into music. The final, refined musical rendition can be compared to the initial visual idea. Can an artistic idea be preserved through these changes of media? Can a non-trivial pattern be envisaged in an artwork, and then still be identified after the change of medium? Here, we consider a contemporary installation and an ensemble musical piece derived from…
Pattern Recognition: The "Postcinema" Seen by William Gibson
2015
Attraverso la lettura di "Pattern Recognition" di William Gibson possiamo rintracciare i caratteri del Postcinema