Through support vector machine algorithms for data classification training, SVMs provide a effective way for analysis of this data.
通过支持向量机训练算法对数据进行分类训练，为分析数据提供有效的手段。
Through support vector machine algorithms for gene expression data classification training, SVMs provide a effective way for analysis of gene expression data.
通过支持向量机训练算法对基因表达数据进行分类训练，为分析基因数据提供有效的手段。
In addition, training people to understand and consistently apply a classification can be time-consuming.
此外，培训人们去理解和一致地应用一种分类是很费时的。
Note that this type of training will generally fit into the decision problem framework because the goal is not to produce a classification but to make decisions that maximize rewards.
需要注意的是，这类训练通常会置于决策问题的框架里，因为它的目标不是产生一个分类系统，而是做出最大回报的决定。
For the training task, the Classification Workbench reports present a lot of information both on the overall KB accuracy and on a per-category basis.
对于训练任务，ClassificationWorkbench会报告大量信息，包括总体知识库精确性和每个目录的精确性。
This name must be used again in the Classification Workbench, where you have to choose a field that contains the document text of your training data.
在ClassificationWorkbench中选择包含训练数据文档文本的字段的地方，必须同样使用这个名称。
Similarly, with machine learning algorithms, a common problem is over-fitting the data and essentially memorizing the training set rather than learning a more general classification technique.
同样，对于机器学习算法，一个通常的问题是过适合(原文为over -fitting，译者注)数据，以及主要记忆训练集，而不是学习过多的一般分类技术。
The classification problem is then to find a good predictor for the class y of any sample of the same distribution (not necessarily from the training set) given only an observation [6]:338.
所谓的分类问题就是指对于相同分布的样本x（可以是训练集以外的样本），都能预知其所属的类。
Minimum Classification Error (MCE) criterion based sub-words weighting parameters estimation algorithm is proposed in which the sub-word weighting parameters are derived by the MCE training.
本文提出了一种基于最小分类错误准则(MCE)的子词权重参数估计算法，通过MCE训练得到子词的权重系数。
The proficiency in classification and selection of Sol-fa and the mastery over training methods and steps of intonation are fundamental prerequisites for learning solfeggio.
对唱名法的分类与选择、音准的训练方法与步骤等内容的熟练掌握是学习视唱练耳的基本前提。
Experimental results show that the method improves the precision of classification effectively and reduces the complexity in training. The overall classification precision reaches 90%.
实验表明，该方法有效地提高了分类准确性，降低了训练的复杂度，分类准确率可达90%。
VQ codebook design is essentially a classification of training vectors.
矢量量化码书设计本质是搜索训练矢量的最佳分类。
How to define training sample size and therefore select classifiers is a problem to solve in actual classification considering the cost of acquisition of samples.
考虑到样本获取的代价性，如何根据训练样本的大小来选择有效分类器是实际分类中需要解决的问题。
This essay describes briefly the conception, formation, production system, basic characteristics, function, classification of football consciousness, its place in football and training principles.
本文简述了足球意识的概念、组成、产生机制、基本特征、功能、分类，以及在足球运动中的地位和培养原则。
The correct classification rate is 100% for training samples by the two methods, and some targets are predicted as potential Sn ore-field.
二种方法对训练样本的分类正确率达100%。据此模型预报了若干个矿点为锡矿区。
An improved design method on pattern classifier based on multi-layer perceptrons (MLP) by means of minimum classification error (MCE) training was proposed.
提出了一种基于最小分类错误(MCE)训练的采用多层感知器(MLP)结构的模式分类器设计方法。
It has payed great attention to effective training of feedforward neural networks when they are used for pattern classification.
前向网络在用于模式分类时，其网络的有效训练一直是一个受到关注的问题。
The support vector machine is a learning algorithm, which has a good classification ability for limited training samples.
支撑矢量机是一种能在训练样本数很少的情况下达到很好分类推广能力的学习算法。
The results of experiment show that the improved algorithm advances the precision of text classification, and reduces the requirement of training scale.
试验结果证明此改进算法能够提高文本分类精度，很好的降低了分类器对训练规模的要求。
This paper presents an efficient training algorithm for probabilistic neural networks using the minimum classification error criterion.
提出了一种基于最小分类错误准则的概率神经网络的训练算法。
By comparison, LVQ network was better than the others in classification ability and training cost, and PNN network in computation load and easy use.
比较而言，学习矢量量化网络在分类能力和训练成本方面更胜一筹，而概率神经网络则在计算负载和易用性方面更好一些。
In the classification experiment, we find that the number of the support vector is far less than the number of the training sample number.
在分类实验中，我们发现支持向量的数量远远小于样本数，这为我们解决大规模数据问题提供了方法。
By training and check up of the stylebook, it's satisfying to predict the rock masses classification in front of the tunnel face.
通过对样本库的训练检验，对掌子面前方围岩类别预报取得了满意的效果。
The classification method USES decomposition strategy to decompose initial problem into a series of two-class classification problems that reduces training scale and enhances training speed.
该方法采用分解策略，将原问题分解为一系列两类分类问题，降低了训练规模，提高了训练速度。
Use the class information of training set to build the model, and extract the feature benefit to classification.
利用训练文档的类信息对文本分类模型进行建模，提取对分类贡献较大的特征。
Further, a hybrid BP algorithm with dead interval of error is derived for training the neural classifier in order to increase training speed and classification accuracy.
此外，提出用带输出误差死区的混合BP算法训练神经元分类器，提高了网络学习训练速度和分类准确性。
The training constructing model and real measurement classification for DOW/ICI main index D were done.
具体对其中的DOW/ICI总指标D进行了训练建模和实测分级。
The training constructing model and real measurement classification for DOW/ICI main index D were done.
具体对其中的DOW/ICI总指标D进行了训练建模和实测分级。
应用推荐