Partitioning for Profit: An Empirical Study of Methods for Handling Unequal Costs of Error in Predictive Data Mining

This paper expands prior work on the Sequential Binary Programming (SBP) algorithm as a framework for cost-sensitive classification. The field of cost-sensitive learning has provided a number of methods to adapt predictive data mining from engineering and hard science applications to those in commerce. This discussion will test theoretical limitations of classical cost-sensitive algorithms empirically and outline the appropriate conditions under which various methods (specifically SBP) should be implemented in favor of others.     

中国观赏虾的产业化开发及展望

论文介绍了目前水族市场上的主要观赏虾品种水晶虾、观赏鳌虾、海水观赏虾,从观赏、生态、经济等方面阐述了观赏虾的开发价值。在对我国观赏虾的苗种来源、幼体培育及观赏虾产业开发现状进行分析的基础上,针对观赏虾产业化过程中存在的问题,提出了通过观赏虾新品种的选育、规模化人工繁殖及产业化养殖的手段来进一步扩大观赏虾市场的途径,并对我国观赏虾的产业化开发前景做出展望,为推动观赏虾产业的发展提供参考。     

湖北省有关封山植树、退耕还林问题的探讨

封山植树、退耕还林是湖北省生态环境建设的重大战略举措。封山植树作为一项系统工程 ,必须解决森林培育方向 ,明确责权利 ,搞好政策支撑、科技支撑 ,保证苗木种质优化 ,正确认识合理利用森林资源与封山植树的关系。退耕还林项目的实施 ,必须从实际出发 ,充分认识退耕坡度、退耕模式等科学研究的重要意义 ,同时保障政策、法律、法规的有力支撑 ,针对资金不足的问题 ,提出生态补偿制度。     

Non-implementation of rational expectations as a perfect Bayesian equilibrium

Summary. We point out several conceptual difficulties of the rational expectations equilibrium concept. In particular we show that such an equilibrium need not be incentive compatible and need not be implementable as a perfect Bayesian equilibrium . A comparison of rational expectations equilibria with the private core is also provided. We conclude that the private core is a more appropriate concept to capture the idea of contracts under asymmetric information.Received: 15 December 2003, Revised: 18 November 2004, JEL Classification Numbers: C71, C72, D5, D82. Correspondence to: Nicholas C. YannelisWe wish to thank Dr A. Hadjiprocopis for his invaluable help with the implementation of Latex in a Unix environment.     

试析古树名木崇拜及其生态意义--以浙江山区为例

古树名木崇拜习俗普遍存在于浙江山区各地。本文探究其历史渊源,叙述了西天目山“大树王”等古树神树的传说,并将崇拜古树名木的主要形式归纳为五种:寄拜、治病、除邪、祛灾及祭祀。随后,探讨了这一习俗在教育人们爱护自然、保护生态,规范人与自然关系行为以及提升整个社会成员保护生态自觉性三个方面的生态意义。     

Asymptotics of the price oscillations of a European call option in a tree model

It is well known that the price of a European vanilla option computed in a binomial tree model converges toward the Black-Scholes price when the time step tends to zero. Moreover, it has been observed that this convergence is of order 1/ n in usual models and that it is oscillatory. In this paper, we compute this oscillatory behavior using asymptotics of Laplace integrals, giving explicitly the first terms of the asymptotics. This allows us to show that there is no asymptotic expansion in the usual sense, but that the rate of convergence is indeed of order 1/ n in the case of usual binomial models since the second term (in     ) vanishes. The next term is of type   C ₂( n )/ n   , with   C ₂( n )  some explicit bounded function of n that has no limit when n tends to infinity.     

沈阳市行道树调查研究

本文主要阐述城市行道树选择的原则及沈阳市行道树应用现状进行分析,并对沈阳市市内五区的行道树进行了调查、分析,提出了改变当前现状,丰富行道树树种的对策和建议。结果表明存在树种单一;常绿树多,落叶树少;行道树的开发利用研究工作十分薄弱等现象,并针对以上问题提出了几点建议。     

虚拟森林建模及其在影视游戏中的应用研究

植物形态的仿真一直是计算机图形学的热点。虚拟森林环境是虚拟现实技术与动漫领域相结合的新型研究领域,其构建复杂的森林对象、表达及分析复杂的森林生长规律的能力为动漫产业研究提供了一个新型的平台。本文主要以植被生长规律为依据,构建并实现面向动漫游戏平台的虚拟森林模型。同时借鉴生物界自然选择和进化机制,从植物种群着手,利用遗传算法模拟虚拟森林中植物个体之间的竞争关系,体现了优胜劣汰的自然选择规律,在一定程度上实现了虚拟森林反演过去、再现现实、预测未来的功能。     

Modeling and predicting U.S. recessions using machine learning techniques

The most representative machine learning techniques are implemented for modeling and forecasting U.S. economic activity and recessions in particular. An elaborate, comprehensive, and comparative framework is employed in order to estimate U.S. recession probabilities. The empirical analysis explores the predictive content of numerous well-followed macroeconomic and financial indicators, but also introduces a set of less-studied predictors. The predictive ability of the underlying models is evaluated using a plethora of statistical evaluation metrics. The results strongly support the application of machine learning over more standard econometric techniques in the area of recession prediction. Specifically, the analysis indicates that penalized Logit regression models, k-nearest neighbors, and Bayesian generalized linear models largely outperform ‘original’ Logit/Probit models in the prediction of U.S. recessions, as they achieve higher predictive accuracy across long-, medium-, and short-term forecast horizons.