Evaluation Characteristics for Estimation of Clothes Becoming

Keiko Isoi, K. Kazama
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Abstract

The purpose of this study is to examine what characterizes certain evaluations from observers who estimate“clothes becoming to each wearer”that depend on the shape of the graph of frequency distribution of the evaluated values.The characteristic means the ability that the difference among clothes becoming to each wearer about their evaluations is able to detect in.36 models were worn in 20 sets of clothes, and the evaluation samples were made from each combimnation.56 observers estimated“clothes becoming to the wearer”in degrees of 1to 7 for every samples.The similar shapes of frequency distribution maps were integrated.They were classified in to four types;“bell”, “flat”, “M”and“No peak”.As for the power of detection, four decision standards were defined from tne structure of the difference in evaluation.And the test of the ratio was done in every decision standard.As a result, “No peak”type showed the highest detection power.The second was“flat”type.The third was“M”type.The fourth was“bell”type.This led to the next discovery.A difference in the distribution form shows a difference in structure of the“becoming”evaluation.The power of detection can be judged by the characteristics of the structure.About“becoming”, the mean of the observers isn't used, but it must think by four distribution types.
服装成型评估的评价特征
本研究的目的是检验观察者根据评估值的频率分布图的形状来估计“衣服适合每个穿着者”的某些评估的特征。这一特性意味着每个穿着者对不同衣服的不同评价能够被检测出来的能力。36位模特穿20套衣服,每种组合制作评价样品。56名观察员估计,每个样品的“衣服适合穿着者”的程度在1到7之间。将相似形状的频率分布图进行整合。它们被分为四种类型:“钟形”、“扁平”、“M形”和“无峰”。在检测能力方面,根据评价差异的结构定义了四个决策标准。在每个决策标准中都进行了比率测试。结果表明,“无峰”型检测功率最高。第二种是“平”型。第三种是“M”型。第四种是“钟”型。这导致了下一个发现。分布形式的不同反映了“成为”评价结构的不同。探测的威力可以通过结构的特性来判断。关于“成为”,不使用观察者的均值,但必须考虑四种分布类型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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