the aim of this study was to investigate the potential association between growth hormone gh/alui and growth hormone receptor ghr/alui polymorphisms with milk yield and reproductive performances in holstein dairy cows in iran. blood samples of 150 holstein cows were collected and their genomic dna was extracted using gene-fanavaran dna extracting kit. fragments of the 428 bp of exon 5 growth ho...

We construct groups in which FV (n) ≁ δ(n). This construction also leads to groups Gk, k ≥ 3 for which δ (n) is not subrecursive. The Dehn function of a group provides a measure of the complexity of the group’s word problem by measuring the difficulty of filling loops in a corresponding complex. A natural generalization is to consider the difficulty of filling higher-dimensional manifolds or cy...

We develop a variant of multiclass logistic regression that achieves three properties: i) We minimize a non-convex surrogate loss which makes the method robust to outliers, ii) our method allows transitioning between non-convex and convex losses by the choice of the parameters, iii) the surrogate loss is Bayes consistent, even in the non-convex case. The algorithm has one weight vector per clas...

This paper reports a preliminary investigation of the use of modern data mining tools for mortgage scoring. Using IBM's Intelligent Miner (a data mining toolbox), we built a model of serious delinquency on a sample of data from Mortgage Information Corpo-ration's Loan Performance System, which contains over 20 million loans with a volume of over $1.6 trillion. Currently, two technologies prevai...

We consider support recovery in the quadratic logistic regression setting – where the target depends on both p linear terms xi and up to p quadratic terms xixj . Quadratic terms enable prediction/modeling of higher-order effects between features and the target, but when incorporated naively may involve solving a very large regression problem. We consider the sparse case, where at most s terms (...

Multiple Logistic Regression Just as in OLS regression, logistic models can include more than one predictor. The analysis options are similar to regression. One can choose to select variables, as with a stepwise procedure, or one can enter the predictors simultaneously, or they can be entered in blocks. Variations of the likelihood ratio test can be conducted in which the chi-square test (G) is...

Logistic regression is the most common method used to model binary response data. When the response is binary, it typically takes the form of 1/0, with 1 generally indicating a success and 0 a failure. However, the actual values that 1 and 0 can take vary widely, depending on the purpose of the study. For example, for a study of the odds of failure in a school setting, 1 may have the value of f...