global warming and predictions of climatic changes additionally put breeding for drought tolerance in the focus of breeding programmes for maize. extensive studies on the existing gene bank collection of the maize research institute “zemun polje“ have been performed with the aim to identify and form initial sources for the development of maize inbreds more tolerant to drought. all accessions (a...

Partial least squares regression on functional data is applied in the context of linear discriminant analysis with binary response. The discriminant coefficient function is then used to compute scores which allow to assign a new curve to one of the two classes. The method is applied to gait data and the results are compared with those given by linear discriminant analysis and logistic regressio...

Discriminant analysis of chemistry and hematology laboratory test results was used to classify patients with and without myocardial infarction in a coronary care unit. We studied 64 patients with myocardial infarction and 70 patients without infarction, using logistic regression, linear and quadratic discriminant analyses on untransformed and logarithmically transformed data. Serum aspartate am...

Fusion is a common approach to improving the performance of speaker recognition systems. Multiple systems using different data, features or algorithms tend to bring complementary contributions to the final decisions being made. It is known that factors such as native language or accent contribute to speaker identity. In this paper, we explore inter-task fusion approaches to incorporating side i...

Mode choice analysis has received the most attention among discrete choice problems in travel behavior literature. Most traditional mode choice models are based on the principle of random utility maximization derived from econometric theory. This paper investigates performance of mode choice analysis with classification methods decision trees, discriminant analysis and multinomial logit. Experi...

3 Basic Classification 3 3.1 Linear Discriminant Analysis . . . . . . . . . . . . . . . . . . . . . . . . . 3 3.1.1 K = 2 Classification . . . . . . . . . . . . . . . . . . . . . . . . . . 4 3.1.2 K > 2 Classification . . . . . . . . . . . . . . . . . . . . . . . . . . 4 3.2 Logistic Regression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 3.2.1 Two Class IRLS . . . . . . . . ...

Speakers’ gender and age-group were predicted using the symbolic information of the X-JToBI prosodic labelling scheme as applied to the Core of the Corpus of Spontaneous Japanese (44 hours, 155 speakers, 201 talks). The correct prediction rate of speaker gender by means of logistic regression analysis was about 80%, and, the correct discrimination rate of speaker age-group (4 groups) by means o...

The credit scoring model development has become a very important issue, as the credit industry is highly competitive. Therefore, considerable credit scoring models have been widely studied in the areas of statistics to improve the accuracy of credit scoring during the past few years. This study constructs a hybrid SVM-based credit scoring models to evaluate the applicant’s credit score accordin...

The assessment of risk of default on credit is important for financial institutions. Logistic regression and discriminant analysis are techniques traditionally used in credit scoring for determining likelihood to default based on consumer application and credit reference agency data. We test support vector machines against these traditional methods on a large credit card database. We find that ...