Research on Algorithm for Mining Negative Association Rules Based on Frequent Pattern Tree

Typical association rules consider only items enumerated in transactions. Such rules are referred to as positive association rules. Negative association rules also consider the same items, but in addition consider negated items （i. e. absent from transactions）. Negative association rules are useful in market-basket analysis to identify products that conflict with each other or products that complement each other. They are also very convenient for associative classifiers, classifiers that build their classification model based on association rules. Indeed, mining for such rules necessitates the examination of an exponentially large search space. Despite their usefulness, very few algorithms to mine them have been proposed to date. In this paper, an algorithm based on FP tree is presented to discover negative association rules.

CONVERGENCERATESIN THESTRONG LAWSOFASYMPTOTICALLY NEGATIVELY ASSOCIATEDRANDOM FIELDS

In this paper, a notion of negative side ρ \|mixing ( ρ\+- \|mixing) which can be regarded as asymptotic negative association is defined, and some Rosenthal type inequalities for ρ\+- \|mixing random fields are established. The complete convergence and almost sure summability on the convergence rates with respect to the strong law of large numbers are also discussed for ρ\+-\| mixing random fields. The results obtained extend those for negatively associated sequences and ρ\+*\| mixing random fields.

Empirical Euclidean likelihood for general estimating equations under association dependence

Empirical Euclidean likelihood for general estimating equations for association dependent processes is investigated. The strong consistency and asymptotic normality of the blockwise maximum empirical Euclidean likelihood estimator are presented. We show that it is more efficient than estimator without blocking. The blockwise empirical Euclidean log-likelihood ratio asymptotically follows a chi-square distribution.

Outlier Detection Method based on Hybrid Rough - Negative Algorithm

This paper discusses on the detection of outliers by hybridizing Rough_Outlier Algorithm with Negative Association Rules. An optimization algorithm named Binary Particle Swarm Optimization is used to improve the computation of Non_Reduct in order to detect outliers.By using Binary PSO algorithm, the rules generated from Rough_Outliers algorithm is optimized, giving significant outliers object detected. The detection ofoutliers process is then enhanced by hybridizing it with Negative Association Rules. Frequent and Infrequent item sets from outlier rules are generated. Results show that the hybrid Rough_Negative algorithm is able to uncover meaningful knowledge of outliers from the frequent and infrequent item sets. These knowledge can then be used by experts in their field of domain for better decision making.

The43,000Growth - associated Protein Functions as a Negative Growth Regulator in Glioma.

Previous molecular analyses of human astrocytomas have identified many genetic changes associated with astrocy-toma formation and progression.In an effort to identify novel gene expression changes associated with astrocytomaformation,which might reveal new potential targets for glioma therapeutic drug design,we used the B8-RAS-transgenic mouse astrocytoma model.Using multiplex gene expression profiling,we found that

Effects of microtopography on spatial point pattern of forest stands on the semi-arid Loess Plateau,China

Microtopography may affect the distribution of forests through its effect on rain redistribution and soil water distribution on the semi-arid Loess Plateau,China.In this study,we investigated the characteristics of microtopography on two shady slopes（slope A,5 hm2,uniform slope;slope B,5 hm2,microtopography slope） and surveyed the height,the diameter at breast height and the location（x,y coordinates） of all selected individual trees（Robinia pseudoacacia Linn.,Pyrus betulifolia Bunge,Populus hopeiensis Hu ＆ Chow,Armeniaca sibirica Lam.,Populus simonii Carr.and Ulmus pumila Linn.） on slope A and slope B in the watersheds of Wuqi county,Shaanxi province.Subsequently,the effects of microtopography on the spatial pattern of forest stands were analyzed using Ripley＇s K（r） function.The results showed that：（1） The maximal aggregation radiuses of the tree species on the uniform slope（slope A） were larger than 40 m,whereas those of the tree species on the microtopography slope（slope B） were smaller than 30 m.（2） On slope B,the spatial association of R.pseudoacacia with P.betulifolia,A.sibirica,P.simonii and U.pumila varied from being strongly negative to positive at microtopography scales.The spatial association of Populus hopeiensis Hu ＆ Chow with U.pumila also varied from being strongly negative to positive at microtopography scales.However,there was no spatial association between P.betulifolia and P.hopeiensis,P.betulifolia and A.sibirica,P.betulifolia and P.simonii,P.betulifolia and U.pumila,P.hopeiensis and A.sibirica,P.hopeiensis and P.simonii,A.sibirica and P.simonii,A.sibirica and U.pumila,and P.simonii and U.pumila.On slope A,the spatial association between tree species were strongly negative.The results suggest that microtopography may shape tree distribution patterns on the semi-arid Loess Plateau.

Central Limit Theorems for Asymptotically Negatively Associated Random Fields

The aim of this paper is to investigate the central limit theorems for asymptotically negatively dependent random fields under lower moment conditions or the Lindeberg condition. Results obtained improve a central limit theorem of Roussas[11]for negatively associated fields and the main results of Su and Chi [18]. and also include a central limit theorem for weakly negatively associated random variables similar to that of Burton et al.[20].

A Berry-Esseen Theorem and a Law of the Iterated Logarithm for Asymptotically Negatively Associated Sequences

Negatively associated sequences have been studied extensively in recent years, Asymptotically negative association is a generalization of negative association, In this paper a Berry Esseen theorem and a law of the iterated logarithm are obtained for asymptotically negatively associated sequences.

Rosenthal type inequalities for asymptotically almost negatively associated random variables and applications

In this paper, we establish some Rosenthal type inequalities for maximum partial sums of asymptotically almost negatively associated random variables, which extend the corresponding results for negatively associated random variables. As applications of these inequalities, by employing the notions of residual Cesàro α-integrability and strong residual Cesàro α-integrability, we derive some results on Lp convergence where 1 < p < 2 and complete convergence. In addition, we estimate the rate of convergence in Marcinkiewicz-Zygmund strong law for partial sums of identically distributed random variables.

Precise Asymptotics in the Law of the Iterated Logarithm of Moving-Average Processes

In this paper, we discuss the moving-average process Xk = ∑i=-∞ ^∞ ai＋kεi, where {εi;-∞ 〈 i 〈 ∞} is a doubly infinite sequence of identically distributed ψ-mixing or negatively associated random variables with mean zeros and finite variances, {ai;-∞ 〈 i 〈 -∞） is an absolutely solutely summable sequence of real numbers.

Spatial point-pattern analysis as a powerful tool in identifying pattern-process relationships in plant ecology: an updated review

Background:Ecological processes such as seedling establishment,biotic interactions,and mortality can leave footprints on species spatial structure that can be detectable through spatial point-pattern analysis(SPPA).Being widely used in plant ecology,SPPA is increasingly carried out to describe biotic interactions and interpret patternprocess relationships.However,some aspects are still subjected to a non-negligible debate such as required sample size(in terms of the number of points and plot area),the link between the low number of points and frequently observed random(or independent)patterns,and relating patterns to processes.In this paper,an overview of SPPA is given based on rich and updated literature providing guidance for ecologists(especially beginners)on summary statistics,uni-/bi-/multivariate analysis,unmarked/marked analysis,types of marks,etc.Some ambiguities in SPPA are also discussed.Results:SPPA has a long history in plant ecology and is based on a large set of summary statistics aiming to describe species spatial patterns.Several mechanisms known to be responsible for species spatial patterns are actually investigated in different biomes and for different species.Natural processes,plant environmental conditions,and human intervention are interrelated and are key drivers of plant spatial distribution.In spite of being not recommended,small sample sizes are more common in SPPA.In some areas,periodic forest inventories and permanent plots are scarce although they are key tools for spatial data availability and plant dynamic monitoring.Conclusion:The spatial position of plants is an interesting source of information that helps to make hypotheses about processes responsible for plant spatial structures.Despite the continuous progress of SPPA,some ambiguities require further clarifications.

Laws of Large Numbers for Cesàro alpha-integrable Random Variables under Dependence Condition AANA or AQSI

Both residual Cesaro alpha-integrability （RCI（α） and strongly residual Cesaro alpha- integrability （SRCI（α）） are two special kinds of extensions to uniform integrability, and both asymptotically almost negative association （AANA） and asymptotically quadrant sub-independence （AQSI） are two special kinds of dependence structures. By relating the RCI（α） property as well as the SRCI（α） property with dependence condition AANA or AQSI, we formulate some tail-integrability conditions under which for appropriate α the RCI（（α） property yields Ll-convergence results and the SRCI（α） property yields strong laws of large numbers, which is the continuation of the corresponding literature.