Logistic regression (LR), discriminant analysis (DA), and neural networks (NN) were used to predict ordered and disordered regions in proteins. Training data were from a set of non-redundant X-ray crystal structures, with the data being partitioned into N-terminal, C-terminal and internal (I) regions. The DA and LR methods gave almost identical 5-cross validation accuracies that averaged to the...

In this paper, we summarize our efforts for the Speakers In The Wild (SITW) challenge, and we present our findings with this new dataset for speaker recognition. Apart from the standard comparison of different SRE systems, we analyze the use of diarization for dealing with audio segments containing multiple speakers, as in part of the newly introduced enrollment and test protocols, diarization ...

Credit scoring has become a very important task as the credit industry has been experiencing double-digit growth rate during the past few decades. The artificial neural network is becoming a very popular alternative in credit scoring models due to its associated memory characteristic and generalization capability. However, the decision of network’s topology, importance of potential input variab...

Marketing problems often involve binary classification of customers into “buyers” versus “non-buyers” or “prefers brand A” versus “prefers brand B”. These cases require binary classification models such as logistic regression, linear, and quadratic discriminant analysis. A promising recent technique for the binary classification problem is the Support Vector Machine (Vapnik (1995)), which has a...

Keywords: Human tibia Binary logistic multivariate discriminant analysis technique Sexing Original article

While i-vectors with probabilistic linear discriminant analysis (PLDA) can achieve state-of-the-art performance in speaker verification, the mismatch caused by acoustic noise remains a key factor affecting system performance. In this paper, a fusion system that combines a multi-condition SNR-independent PLDA model and a mixture of SNR-dependent PLDA models is proposed to make speaker verificati...

The current situation in environmental monitoring is characterized by increasing amount of data from monitoring networks together with increasing requirements on joining of these data from various sources in comprehensive databases and their usage for decision support in environmental protection and management. The automated analysis of such a heterogeneous datasets is a complicated process, ri...

Neural nets have become one of the most important tools using in credit scoring. Credit scoring is regarded as a core appraised tool of commercial banks during the last few decades. The purpose of this paper is to investigate the ability of neural nets, such as probabilistic neural nets and multi-layer feed-forward nets, and conventional techniques such as, discriminant analysis, probit analysi...

We present a learning algorithmic approach to the problem of recognzing the file types of file fragments, with the purpose of applying this to “file carving”, the reconstruction of partially erased files on disk into whole files. We do so through the use of 257 calculated features of an input fragment, applying the Support Vector Machine, Multinomial Naive Bayes, and Linear Discriminant Analysi...

The main objective of this study is to determine the factors influencing the cloud computing adoption by Small and Medium sized Enterprises (SMEs). Based on two dominant theories in the field of diffusion of innovation, a conceptual model is proposed. In order to test the model empirically, an online survey was designed and launched. Decision makers of 50 SMEs agreed to participate in this surv...