Logistic Model Trees

Tree induction methods and linear models are popular techniques for supervised learning tasks, both for the prediction of nominal classes and numeric values. For predicting numeric quantities, there has been work on combining these two schemes into model trees, i.e. trees that contain linear regression functions at the leaves. In this paper, we present an algorithm that adapts this idea for classification problems, using logistic regression instead of linear regression. We use a stagewise fitting process to construct the logistic regression models that can select relevant attributes in the data in a natural way, and show how this approach can be used to build the logistic regression models at the leaves by incrementally refining those constructed at higher levels in the tree. We compare the performance of our algorithm to several other state-of-the-art learning schemes on 36 benchmark UCI datasets, and show that it produces accurate and compact classifiers.Editor Johannes FürnkranzThis is an extended version of a paper that appeared in the Proceedings of the 14th European Conference on Machine Learning (Landwehr et al., 2003).     

Logistic阻滞增长模型的计算机模拟

将Logistic阻滞增长模型的差分形式进行简化,对Logistic模型的简化差分形式进行迭代求解,做出了随固有增长率r的变化,序列狖yk狚收敛、2倍周期、4倍周期……直至一片混乱的图形。以参数b为横坐标、序列狖yk狚的收敛点为纵坐标,用MATLAB数学软件模拟展示了这一简单差分方程从收敛、分叉、2n倍周期收敛进入混沌现象的过程。     

基于非线性Logistic模型的改进UDEED算法

针对UDEED算法中线性Logistic模型分类预测准确率较低的问题,基于泰勒展开式,提出一种多项式核的非线性Logistic模型改进算法。研究非线性Logistic模型的核函数参数估计方法,更新损失函数的计算规则,并利用梯度下降法求解改进UDEED模型,实现数据集的分类预测。实验结果表明,与UDEED算法相比,改进算法提高了分类预测的准确率。     

基于同态加密的多分类Logistic回归模型

随着计算能力的发展,机器学习得到了广泛的应用,数据的安全问题也成为一个重要问题.同态加密技术可以在不泄露明文信息的情况下,对密文进行运算并在解密后得到与在明文上执行相应运算一致的结果.因此,同态加密是一种可行的有潜力的数据安全外包解决方案.为了解决现实生活中出现的多分类问题,本文基于Cheon等提出的HEAAN同态加密方案,提出了一种能有效保护数据隐私的多分类Logistic回归模型,采用"一对其余"的拆解策略,通过训练多个分类器,将二分类Logistic回归模型推广到多分类.数据持有者可以将数据加密后发送给服务器,服务器使用多分类Logistic回归模型对加密数据进行训练,并将结果传回数据持有者,数据持有者解密结果后可以用来对多分类数据进行预测,整个过程中不会有隐私被泄露.本文通过对UCI的Dermatology和Iris数据集进行了实验,测试模型的性能.Dermatology数据集包含358条样本, 34个特征属性,分为6个类别,训练时间约为36.70分钟,准确率达到77.18%,与明文计算的准确率一致.实验验证了本文的模型在效率和准确率方面的可行性.     

基于Web Service技术的综合物流模型

对Web Service技术的基本特征进行了探讨,并应用Web Service和SOAP的开放特性,设计企业综合物流系统,解决了企业物流跨网络、跨平台数据通信以及系统间灵活集成的问题。     

城市车辆配送线路设计的模型与算法

文章建立了城市车辆配送的多旅行商问题(MTSP)模型,设计了一个新的遗传算法,用2Opt算子改进解的总距离,用贪心交叉算子提供变异功能,计算实例表明了该算法的有效性。     

Stability of the Logistic Population Model with Delayed Environmental Response

The population dynamics model , was considered. For this model with uniform distribution of delays and a _n = 0, nonnegativeness and convexity of the sequence a _k (0 k n) was shown to be the sufficient stability condition. Therefore, there is no need to constrain the reproduction rate and the mean delay .     

棉花物流运输路径建模及仿真应用研究

分析我国棉花物流运输现状及问题,以降低运输成本为目标,综合考虑发货点、收货点、运输方式、油费、路桥费、运输时间等因素,建立棉花运输路径模型,运用前k条最短路径算法求解最优路径.     

可的物流中心参观记

在第七届海鼎现代商业管理用户研讨会期间,记者随部分会议代表参观了上海可的便利店的物流中心,亲身感受可的高度自动化、信息化的物流管理是如何在其走向中国便利店第一品牌的道路上,奠定强大的基础设施支持的。     

基于安全认证模型的物流信息管理系统的设计与实现

该文在分析基于Internet的物流信息系统需求的基础上,采用JavaTMEE体系架构和WebServieces技术,提出了一个基于安全认证的物流信息管理系统模型,设计并实现了物流信息管理系统。该系统已在成都市统计局得到应用,系统安全性得到了有效的保障,应用效果良好。     

一种物流云系统的架构方法

为实现物流领域云服务,满足物流产业相关企业对云服务个性化,快速开发和多样化应用的需求,在云计算机应用架构的原理基础上,根据现代物流企业对物流云服务的特点,提出了一种集底层软硬件管理平台、云服务应用环境平台、云服务开发平台等为一体的物流云PaaS平台架构.讨论和分析了该架构的设计原理和实施细节,为进一步搭建物流领域多样化的SaaS应用提供了快速开发、统一协调和调度的平台,进而满足用户“一站式”个性化服务需求.     

如何用经验Logistic回归方法估计Rasch模型中参数

将经验Logistic回归方法用于项目反应理论中Rasch模型的参数估计,通过蒙特卡洛模拟表明这种方法对项目参数的估计较好,这种方法是对极大似然估计方法的不足的一种补充。     

Self-Organization in a Parametrically Coupled Logistic Map Network: A Model for Information Processing in the Visual Cortex

In this paper, a new model seeking to emulate the way the visual cortex processes information and interacts with subcortical areas to produce higher level brain functions is described. We developed a macroscopic approach that incorporates salient attributes of the cortex based on combining tools of nonlinear dynamics, information theory, and the known organizational and anatomical features of cortex. Justifications for this approach and demonstration of its effectiveness are presented. We also demonstrate certain capabilities of this model in producing efficient sparse representations and providing the cortical computational maps.     

Logistic map neural modelling: A theoretical foundation

The aim of this paper is to establish a theoretical framework for the modelling and simulation of chaotic attractors using neural networks. The attractor paradigm in this paper is the logistic map, which is modelled via neural networks in the convergence, periodic and chaotic regions. It is proved that, under certain conditions, the function simulated by the neural model is actually the logistic map with a different value of the λ parameter from the theoretical value. A two-dimensional system is defined and studied, facilitating the generation of the theoretical time series and the associated simulation error. The fixed points of periods p = 1 and p = 2 are identified and studied with respect to their stability. For higher period values, a theorem concerning the periodicity of the simulation error is postulated and proved. The minimum simulation error value is calculated using analytical methods, and the chaotic nature of the system with respect to Lyapunov exponents is described. Conclusions are discussed with respect to the experimental results obtained by the simulation models.     

A Fast Dual Algorithm for Kernel Logistic Regression

This paper gives a new iterative algorithm for kernel logistic regression. It is based on the solution of a dual problem using ideas similar to those of the Sequential Minimal Optimization algorithm for Support Vector Machines. Asymptotic convergence of the algorithm is proved. Computational experiments show that the algorithm is robust and fast. The algorithmic ideas can also be used to give a fast dual algorithm for solving the optimization problem arising in the inner loop of Gaussian Process classifiers. Editor: Shai Ben-David     

基于Logistic回归模型的藏文文本分类研究与实现

文本分类是信息处理领域的核心研究内容,在自动检索和文本过滤等研究领域中被广泛使用。本次研究主要是基于Logistic回归模型分类器对藏文文本进行分类,其核心思想是首先对藏文语料进行收集和预处理,且利用信息增益算法和欧式距离分别对文本特征进行选择与提取;其次构造Logistic回归模型分类器;最后测试和分析分类的准确率、召回率和F1值,同时,对Logistic算法和Gaussian NB算法进行分类性能对比,结果显示Logistic算法具有较好的分类效果。     

基于虚拟现实的军用后勤装备维修训练系统模型设计

通过研究分析虚拟现实理论和特点,结合后勤装备维修训练系统要素和具体要求,探索一种适应部队信息化建设发展的数字化维修训练系统,即基于虚拟现实的后勤装备虚拟维修训练系统。从系统模型组织结构入手,深入分析了各层次内涵,为建立具体装备的虚拟维修训练系统提供了理论基础。     

日本的物流战略

本文通过对新时期日本物流战略思想、相关因素的阐述以及对物流领域一些领先的生产、流通企业的典型事例分析,说明了有效的物流管理在企业经营中的重要性.     

Logistic混沌映射

混沌理论是研究非线性动力学系统随时间变化的规律。由于混沌系统具有很多优良特性,便将其逐渐应用到密码学及密码分析等学科中。在简述混沌的基础上介绍了一维Logistic混沌映射由倍周期分岔达到混沌的过程,并分析了一些复杂动力学行为。最后将一维Logistic混沌映射应用到图像加密中,并通过仿真实验检验算法的安全性及优越性。