小样本

在合用的小样本中高等真菌的一种惊奇性状是同形种或姊妹种的数量。

A surprising feature of the higher fungi , in the small sample available , is the number of cryptic or sibling species .

STAR模型中退势单位根检验的小样本性质研究

The Small Sample Properties for De-trending Unit Root Tests in STAR Frameworks

由于使用结构风险最小化原则代替经验风险最小化原则，使它较好的解决了小样本情况下的学习问题。

They can solve small-sample learning problems better by using structural risk minimization in place of experiential risk minimization .

小样本条件下BP网络对滑动轴承材料磨损系数的预测研究

BP Network-based Prediction of Abrasion Coefficient of Sliding Bear under Small Sample Data

基于BP神经网络的小样本星图识别方法

Recognition algorithm for star pattern of little swatch based on BP neural network

其二是基于分级聚类和决策树思想构建的多类SVM算法，介绍了算法的思想和具体实现，在小样本情况下对两种算法进行了应用。

Second is multi-class algorithm based on hierarchical clustering and decision tree .

Logistic响应分布中刻度参数的中、小样本推断

Inference for the scale parameter of logistic response distribution with moderate or small sample sizes

统计学习理论（Statisticallearningtheory或SLT）是一种专门研究小样本情况下机器学习规律的理论，它具有完备的理论基础。

Statistical Learning Theory ( SLT ) is a theory , which research the machine study specially in small samples .

基于PSO的Fisher准则下小样本最佳鉴别变换

Small Sample Optimal Discriminant Transform Based on PSO under Fisher Criterion

系统研究了SVM的分类算法，建立了基于SVM的小样本故障诊断模型。

Study the algorithm of SVM classification and establish small samples fault diagnosis model based on SVM .

其缺点是对于同样的数据，R法较其他方法的抽样误差大，而且在小样本中估计值往往有偏。

Disadvantages of Method R include a larger sampling variance than other methods for the same data , and biased estimates in small datasets .

小样本情况下Fisher线性鉴别分析的理论及其验证

Theory of Fisher Linear Discriminant Analysis for Small Sample Size Problem and Its Verification

在小样本条件下直接LDA的理论分析

Theoretical Analysis of Direct LDA in Small Sample Size Problem

方法用正态分布小样本容量的简化检验（A法）和方差检验（B法）来判定两种测定方法所得结果的异同。

Methods The simplified test of normal distribution ( method A ) and analysis of variance ( method B ) were adopted to judge if the two testing methods have variation .

由于依据结构风险最小化原则，SVM较好地解决了小样本、非线性、高维学习问题，成为了当前数据挖掘领域和机器学习界的研究热点。

As for structural risk minimization principle , SVM has a better solution to small sample , nonlinear , high-dimensional learning problems .

支持向量机（SVM）分类器能较好地解决小样本、非线性、高维等分类问题，具有很强的实用性。

Support vector machine can solve the classification problem with small samples , nonlinear and high dimensions , which has strong practicability .

小样本DF统计量的分布特征

Distribution of Small Sample DF Statistic

论文结合了粗集的属性约简和SVM的小样本非线性等优点，提高了系统运行速度以及预测精度，从而达到对房地产投资全程的风险进行分析预测。

This paper combines the rough set attribute reduction to eliminate redundancy , which improve the system operating speed and precision of prediction .

结果表明，基于均匀设计、MATLAB建模与优化程序的小样本数据挖掘在氧化镍纳米晶合成试验中得到了成功的应用。

The results showed that the data mining base on uniform design and MATLAB programs of modeling and optimization was applied to synthesis of nanometer nickel oxide successfully .

针对测量仪器校准间隔的优化问题，根据校准数据非线性、小样本的特点，提出了一种基于新陈代谢GM（1,1）模型的校准间隔预测方法。

To optimize the calibration interval of a measuring instrument , a prediction method based on the renewal GM ( 1,1 ) model is put forward .

基于局部核函数与全局核函数支持向量回归优化小样本QSAR建模

Improve performance of SVR model on small sample QSAR study with local kernel and global kernel

基于小样本容量的IRT参数估计方法比较研究

Comparison among Parameter Estimation Methods Based on Small Sample under Item Response Theory

用模糊综合评判方法与BAYES理论相结合，给出由小样本试验数据确定岩土参数的概率分布。

By combining BAYES theory with fuzzy comprehension evaluation method , this paper suggests a new method to determine the distribution of rock parameters .

而且SVR方法可以克服BP网络过拟合的问题，更适于小样本高参量的问题。

And the SVR method can overcome the over-fit problem so as it is more suitable for the problem with few samples and many variables .

利用所提出的特征，采用适合小样本分类问题的支持向量机（SVM）对足球视频镜头分类。

Support vector machines ( SVMs ) which suit to classification problem for tiny samples is designed for different shot types through the features extracted by the method .

传统的方法是利用BP神经网络对产物浓度进行预测，本文对这两种方法进行了结果对比，证明了在小样本情况下利用支持向量机方法具有更好的预测性。

Traditional method was using BP neural network to predict the data , the thesis compared both of the two methods and proved the advantage of SVM when dealing with small sample data .

高维小样本情况下如何有效地求得理想的Fisher鉴别矢量是非常困难且急待解决的问题。

How to get the optimal Fisher discriminant vectors efficiently in the case of small number samples is a very difficult and critical problem .

该文基于广义的Fisher线性判别准则，将投影变换、同构变换和压缩变换相结合，解决了这个问题，完善了小样本情况下线性鉴别分析理论。

Based on the generalized Fisher linear discriminant criterion , this problem is solved by combining projection transform , isomorphic mapping and compressed transform .

在小样本观测数据情况下，研究利用日地月方位信息和日月星历表进行航天器自主导航以及利用DSP实现航天器自主导航器的技术。

The orientation information of the sun , the moon and the earth , together with ephemeris are utilized to develop autonomous navigation algorithm , as well as its realization by DSP hardware .

在小样本的数据库上用Fisher线性分类器验证所研究算法的性能，正确分类率为79.17%。

Fisher Linear Classifier is used to validate the performance of the proposed algorithm on small database samples and the correct classification rate is 79.17 % .