We show that the widely used Kendall tau correlation coefficient, and the related Mallows kernel, are positive definite kernels for permutations. They offer computationally attractive alternatives to more complex kernels on the symmetric group to learn from rankings, or learn to rank. We show how to extend these kernels to partial rankings, multivariate rankings and uncertain rankings. Examples...

Comparing and ranking information is an important topic in social and information sciences, and in particular on the web. Its objective is to measure the difference of the preferences of voters on a set of candidates and to compute a consensus ranking. Commonly, each voter provides a total order of all candidates. In this work we consider the generalization of total orders and bucket orders to ...

The Kendall (1955) rank correlation coefficient evaluates the degree of similarity between two sets of ranks given to a same set of objects. This coefficient depends upon the number of inversions of pairs of objects which would be needed to transform one rank order into the other. In order to do so, each rank order is represented by the set of all pairs of objects (e.g., [a,b] and [b,a] are the...

The Equilibrium Line Altitude (ELA) is a significant indicator of the changing climate and glacial dynamics. Trend equilibrium line altitude has been analysed for period 1979/80 to 2012/13 in Naradu Valley, western Himalaya. clear effect valley’s increased temperature can be seen on ELA trend. temperature, precipitation few years data have used as an input parameters develop multiple linear reg...

The Mann-Kendall test is a commonly-used nonparametric test for time trend. However, the standard P-values obtained from it are based on an assumption of independence between observations (since the theory is that of the Kendall correlation). However, observations in time series are often autocorrelated: knowing that one observation is larger than the mean may tell you that the next observation...

This paper studies the application of principal component analysis, multiple polynomial regression, and artificial neural network ANN techniques to the quantitative analysis of binary mixture of dye solution. The binary mixtures of three textile dyes including blue, red and yellow colors were analyzed by PCA-Multiple polynomial Regression and PCA-Artificial Neural network PCA-ANN methods. The o...

conclusions addressing and removing explainable patterns of syndromic data on meningitis is necessary to timely and accurately detection of meningitis epidemics. it was concluded that decomposition methods had better performance compared to the model based ones. background meningitis is one of the most disturbing infectious diseases due to mortality, morbidity and its ability to cause epidemic....