Применение метода условных деревьев решений к моделированию выбора школы родителями
In the article we suggest a method for analyzing situations of choice, which is novel for sociology - the method of conditional decision trees. We describe the logic of the method, applying it to the case of parental choice of school in two urban districts of Saint-Petersburg. We show that decision trees work well for detecting groups that follow different decision making strategies. This can be an efficient tool for modeling and interpretation of the logic of choice. The method outperforms the traditional modeling by means of logistic regression, as it allows for assessing homogeneity of preferences (choices) of the groups detected, instead of simply finding the key factors related to choice. We recommend combining regression analysis with decision trees modeling in all kinds of academic and applied research studying complicated choices.
The paper makes a brief introduction into multiple classifier systems and describes a particular algorithm which improves classification accuracy by making a recommendation of an algorithm to an object. This recommendation is done under a hypothesis that a classifier is likely to predict the label of the object correctly if it has correctly classified its neighbors. The process of assigning a classifier to each object involves here the apparatus of Formal Concept Analysis. We explain the principle of the algorithm on a toy example and describe experiments with real-world datasets.
In this study a CHAID-based approach to detecting classification accuracy heterogeneity across segments of observations is proposed. This helps to solve some important problems, facing a model-builder: (1) How to automatically detect segments in which the model significantly underperforms? and (2) How to incorporate the knowledge about classification accuracy heterogeneity across segments to partition observations in order to achieve better predictive accuracy? The approach was applied to churn data from the UCI Repository of Machine Learning Databases. By splitting the data set into four parts, which are based on the decision tree, and building a separate logistic regression scoring model for each segment we increased the accuracy by more than 7 percentage points on the test sample. Significant increase in recall and precision was also observed. It was shown that different segments may have absolutely different churn predictors. Therefore such a partitioning gives a better insight into factors influencing customer behavior.
Procedure for the simulation of the advances in EGE from mathematics is considered. For some tasks the important predictors are obtained. The models of binary logistics regression and ordinal regression for the prediction of probabilities of solution of task are built.
Symbolic classifiers allow for solving classification task and provide the reason for the classifier decision. Such classifiers were studied by a large number of researchers and known under a number of names including tests, JSM-hypotheses, version spaces, emerging patterns, proper predictors of a target class, representative sets etc. Here we consider such classifiers with restriction on counter-examples and discuss them in terms of pattern structures. We show how such classifiers are related. In particular, we discuss the equivalence between good maximally redundant tests and minimal JSM-hyposethes and between minimal representations of version spaces and good irredundant tests.
This book constitutes the refereed proceedings of the 6th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2014, held in Montreal, QC, Canada, in October 2014. The 24 revised full papers presented were carefully reviewed and selected from 37 submissions for inclusion in this volume. They cover a large range of topics in the field of learning algorithms and architectures and discussing the latest research, results, and ideas in these areas.
This volume is the first of its kind to offer a detailed, monographic treatment of Semitic genealogical classification. The introduction describes the author's methodological framework and surveys the history of the subgrouping discussion in Semitic linguistics, and the first chapter provides a detailed description of the proto-Semitic basic vocabulary. Each of its seven main chapters deals with one of the key issues of the Semitic subgrouping debate: the East/West dichotomy, the Central Semitic hypothesis, the North West Semitic subgroup, the Canaanite affiliation of Ugaritic, the historical unity of Aramaic, and the diagnostic features of Ethiopian Semitic and of Modern South Arabian. The book aims at a balanced account of all evidence pertinent to the subgrouping discussion, but its main focus is on the diagnostic lexical features, heavily neglected in the majority of earlier studies dealing with this subject. The author tries to assess the subgrouping potential of the vocabulary using various methods of its diachronic stratification. The hundreds of etymological comparisons given throughout the book can be conveniently accessed through detailed lexical indices.
In 2006, Russia amended its competition law and added the concepts of ‘collective dominance’ and its abuse. This was seen as an attempt to address the common problem of ‘conscious parallelism’ among firms in concentrated industries. Critics feared that the enforcement of this provision would become tantamount to government regulation of prices. In this paper we examine the enforcement experience to date, looking especially closely at sanctions imposed on firms in the oil industry. Some difficulties and complications experienced in enforcement are analysed, and some alternative strategies for addressing anticompetitive behaviour in concentrated industries discussed.
This article is talking about state management and cultural policy, their nature and content in term of the new tendency - development of postindustrial society. It mentioned here, that at the moment cultural policy is the base of regional political activity and that regions can get strong competitive advantage if they are able to implement cultural policy successfully. All these trends can produce elements of new economic development.