The Kolmogorov-Smirnov (KS) test is popularly used in many applications, such as anomaly detection, astronomy, database security and AI systems. One challenge remained untouched how we can obtain an explanation on why a set fails the KS test. In this paper, tackle problem of producing counterfactual explanations for data failing Concept-wise, propose notion most comprehensible explanations, whi...

The purpose of this study is to test The Weak Form Efficient Market Hypothesis in Dhaka’s Stock Market. The study examined the distribution of equity returns by dividing the sample period into two sub periods of daily DSE General Index (DGEN) and sub periods are sample-1(2004-2007), and sample-2 (2008-2012). Also, monthly general index starting from 1990 to 2012 are taken as sample to test the ...

A filter algorithm using F-measure has been used with feature redundancy removal based on the Kolmogorov-Smirnov (KS) test for rough equality of statistical distributions. As a result computationally efficient K-S CorrelationBased Selection algorithm has been developed and tested on three high-dimensional microarray datasets using four types of classifiers. Results are quite encouraging and sev...

By using the brute force algorithm, the application of the two-dimensional two-sample Kolmogorov–Smirnov test can be prohibitively computationally expensive. Thus a fast algorithm for computing the two-sample Kolmogorov–Smirnov test statistic is proposed to alleviate this problem. The newly proposed algorithm is O(n) times more efficient than the brute force algorithm, where n is the sum of the...

In this paper, we are interested in extending the classical KolmogorovSmirnov homogeneity test to compare two samples of interval-valued observed measurements. In such a case, the test result is interval-valued, and one major difficulty is to find the bounds of this set. We propose a very efficient computational method for approximating these bounds by using a p-box (pairs of upper and lower cu...

When a reliability analysis, survival analysis, or discrete-event simulation input modeling analysis is performed, it is typically the case that a modeler collects data associated with some system under consideration. Although this raw data provides an initial insight into the stochastic elements of the system, often it is desirable to construct a model of the system which is tractable for math...