Feature selection has been proven to be efficient in preparing high dimensional data for data mining and machine learning. As most data is unlabeled, unsupervised feature selection has attracted more and more attention in recent years. Discriminant analysis has been proven to be a powerful technique to select discriminative features for supervised feature selection. To apply discriminant analys...

This article presents an unsupervised morphological analysis algorithm to segment words into roots and affixes. The algorithm relies on word occurrences in a given dataset. Target languages are English, Finnish, and Turkish, but the algorithm can be used to segment any word from any language given the wordlists acquired from a corpus consisting of words and word occurrences. In each iteration, ...

We extend the unsupervised morpheme segmentation method Morfessor Baseline to account for the linguistic phenomenon of allomorphy, where one morpheme has several different surface forms. Our method discovers common base forms for allomorphs from an unannotated corpus. We evaluate the method by participating in the Morpho Challenge 2008 competition 1, where inferred analyses are compared against...

high through put sequencing of single nucleotide polymorphisms (snp) has revolutionized the fine scale analysis of the population structure in different species. various methods have been proposed and used for the study of population structure using whole-genome marker data that each has advantages and disadvantages with respect to their characteristics. super paramagnetic clustering (spc) whic...

Most scientific disciplinesgenerate experimental data from an observed system about which we have may have little understanding of the data generating function. It is attractive, therefore, for an analysis system to break a complex dataset intoa series of piecewise similar groups or structures, each of which may then be regarded as a separate data state, for example, thus reducing overall data ...

Recognition of human gestures is important for analysis and indexing of video. To recognize human gestures on video, generally a large number of training examples for each individual gesture must be collected. This is a labor-intensive and error-prone process and is only feasible for a limited set of gestures. In this paper, we present an approach for automatically segmenting sequences of natur...

In this paper, we investigate the application of an unsupervised extension of the recently proposed k–windows clustering algorithm on gene expression microarray data. The k–windows algorithm is used both to identify sets of genes according to their expression in a set of samples, and to cluster samples into homogeneous groups. Experimental results and comparisons indicate that this is a promisi...

Large data sets delivered by imaging spectrometers are interesting in many ways in the Planetary Sciences. Due to the size of the data, which often prohibits conventional exploratory data analysis, unsupervised analysis methods could be a way of gathering interesting information contained in the data. In this work, we investigate some of the opportunities and limitations of unsupervised analysi...

Feature selection is effective in removing irrelevant data. However, the result of feature selection in unsupervised learning is not as satisfying as that in supervised learning. In this paper, we propose a novel methodology ULAC (Feature Selection for Unsupervised Learning Based on Attribute Correlation Analysis and Clustering Algorithm) to identify important features for unsupervised learning...