In this paper we present a generative latent variable model for rating-based collaborative filtering called the User Rating Profile model (URP). The generative process which underlies URP is designed to produce complete user rating profiles, an assignment of one rating to each item for each user. Our model represents each user as a mixture of user attitudes, and the mixing proportions are distr...

Identifying sex of hatchling turtles is difficult because juveniles are not obviously externally dimorphic, and current techniques to identify sex are often logistically unfeasible for field studies. We demonstrate a widely applicable and inexpensive alternative to detect subtle but significant sexual dimorphism in hatchlings, using landmark-based geometric morphometric methods. With this appro...

The Kernel Fisher’s Discriminant (KFD) is a non-linear classifier which has proven to be powerful and competitive to several state-of-the-art classifiers. Its main ingredient is the kernel trick which allows the efficient computation of Fisher’s Linear Discriminant in feature space. However, it is assuming equal covariance structure for all transformed classes, which is not true in many applica...

Logistic regression is employed to search the optimal combination of multiple markers that can discriminate ovarian cancers from benign by Luminex assay test of the patient sera. To verify the selection performance, three other classification methods were also tested including t-test, genetic algorithm, and random forest. The chosen combinations from each of the four methods were evaluated agai...

Current work in author identification is primarily directed towards music classification. Identification of artists by analyzing features of their work has recently gained interest. As a multiclass classification problem, potentially applicable machine learning approaches to the problem are numerous. We propose to extend present work in this area, which uses Naïve Bayes classifiers and multi-cl...

Credit Decisions are extremely vital for any type of financial institution because it can stimulate huge financial losses generated from defaulters. A number of banks use judgmental decisions, means credit analysts go through every application separately and other banks use credit scoring system or combination of both. Credit scoring system uses many types of statistical models. But recently, p...

eurotia ceratoides (l.) c. a. mey is an important plant species in semi-arid landsin iran. new approaches are required to determine the distribution of this plant species. forthis reason, geographical distributions of eurotia ceratoides were assessed using threedifferent models including: multiple discriminant analysis (mda), ecological niche factoranalysis (enfa) and logistic regression (lr). ...

Predicting business failure of listed companies is a hot topic because of the emergency of financial crisis in developed countries recently. The two classical statistical methods of multivariate discriminant analysis (MDA) and logistic regression (logit) have taken a key role in the area of business failure prediction (BFP). However, they are frequently criticized for the relative low predictiv...

Classification and prediction in agricultural systems are quite useful for effective planning. In this paper, logistic regression modeling has been employed for classification purposes on data pertaining to the area of agricultural ergonomics. Presence or absence of discomfort for the farm labourers in operating farm machineries has been considered as the dependent variable and associated quant...

We present an empirical investigation of the modeling techniques for identifying fault-prone software components early in the software life cycle. Using software complexity measures, the techniques build models which classify components as likely to contain faults or not. The modeling techniques applied in this study cover the main classification paradigms, including principal component analysi...