A Comparison between Squared Error and Relative Entropy Metrics Using Several Optimization Algorithms
نویسنده
چکیده
Convergence rat es and generalization performance are compared for the squared error metric and a relat ive entropy metric on a contiguity problem using several optimization algorithms. The relat ive entropy measure converged to a good solution slight ly more often than the squared error metric given the same distribution of init ial weights . However, where the results differed, the squared error metric converged on average more rapidly to solutions th at generalized better to the test data. These results are not in complete agreement with some results previously published.
منابع مشابه
Tsallis Entropy for Geometry Simplification
This paper presents a study and a comparison of the use of different information-theoretic measures for polygonal mesh simplification. Generalized measures from Information Theory such as Havrda–Charvát–Tsallis entropy and mutual information have been applied. These measures have been used in the error metric of a surface simplification algorithm. We demonstrate that these measures are useful f...
متن کاملBi-objective optimization of multi-server intermodal hub-location-allocation problem in congested systems: modeling and solution
A new multi-objective intermodal hub-location-allocation problem is modeled in this paper in which both the origin and the destination hub facilities are modeled as an M/M/m queuing system. The problem is being formulated as a constrained bi-objective optimization model to minimize the total costs as well as minimizing the total system time. A small-size problem is solved on the GAMS software t...
متن کاملOn the Difficulty of Inferring Gene Regulatory Networks: A Study of the Fitness Landscape Generated by Relative Squared Error
Inferring gene regulatory networks from expression profiles is a challenging problem that has been tackled using many different approaches. When posed as an optimization problem, the typical goal is to minimize the value of an error measure, such as the relative squared error, between the real profiles and those generated with a model whose parameters are to be optimized. In this paper, we use ...
متن کاملEvaluation of remote sensing indicators in drought monitoring using machine learning algorithms (Case study: Marivan city)
Remote sensing indices are used to analyze the Spatio-temporal distribution of drought conditions and to identify the severity of drought. This study, using various drought indices generated from Madis and TRMM satellite data extracted from Google Earth Engine (GEE) platform. Drought conditions in Marivan city from February to November for the years 2001 to 2017 were analyzed based on spatial a...
متن کاملAn Empirical Comparison of Supervised Learning Algorithms Using Different Performance Metrics
We present results from a large-scale empirical comparison between ten learning methods: SVMs, neural nets, logistic regression, naive bayes, memory-based learning, random forests, decision trees, bagged trees, boosted trees, and boosted stumps. We evaluate the methods on binary classification problems using nine performance criteria: accuracy, squared error, cross-entropy, ROC Area, F-score, p...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Complex Systems
دوره 6 شماره
صفحات -
تاریخ انتشار 1992