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训练集

网络training set; train set; training data

训练集

网络释义

训练集

training set

训练集(Training set) 由一组数据库记录或元组构成，每个记录是一个由有关字段值组成的特征向量，我们把这些字段称做属性(A…

train set

[综] 训练集(train set) 验证集(validation set) 测试集(test set) [综] 粒子滤波 [zz] 直角坐标系的平移和旋转 [zz] Dynamic Tim...

training data

RDRRemote Data Replicate远程数据备份_翻译 ... 数据链： data link 训练集： training data 元数据： Meta-data ...

TRAINING EXPERIENCE

...领域 2副主题 2定义学习任务 3设计学习系统 3训练集（TRAINING EXPERIENCE） 4选择目标函数 4可能的目标函数定义V(B…

brown.train

...先对这个语料库进行划分，从中选取前55340句作为训练集(brown.train)，选取剩余的2000句作为测试集(brown.test)，现在我 …

training images

․假设色调H为人脸特徵依据, 以训练集(training images)测得皮肤色之色调范围可能显得零碎; 吾人可利用形态学的opening与closi…

例句：

In short , given a training set , there are always at least two equally plausible, but totally opposite, generalizations that could be made.

总之，对于一个训练集，总是可以归纳出至少两个（形式）近似的，但完全相反的等式。

It should be stressed that the approximation capabilities of the RNN are limited by the number of training sets available .

应该强调的是，RNN 逼近能力的数量是有限的训练集可得到的。

In the experiment, through changing the training size and language composition the performance of CLTC can be verified .

并通过改变训练集样本大小及语言构成来验证模型的分类性能。

The work capitalized on public hand-classified network dataset and used it to train and tested the supervised SVM traffic classifier .

使用公开的人工标注数据集作为训练集和测试集，通过有监督学习构建支持向量机流量分类器。

If, for instance , you only have 20 samples, there's not much data to use for a training set and still leave a significant test set .

比如，你现在仅仅只有 20 个样本，对于训练集和有效的测试集来说，没有太多的数据。

But learning the training set well is not necessarily the best thing to do .

但是，学习训练集表现良好并不一定是件好事。

This set of samples is called the training set .

这样的样本集称作训练集。

for a balanced training set , it proposes an entropy-based semi-supervised learning algorithm . 3.

而对于平衡训练集，可以直接采用基于熵的半监督学习算法。

Both the sampling position and the window of training set in the long tail of traffic are studied .

基于该分析模型，研究分类算法中训练集采集位置和规模大小的选取。

First find the optimal window estimated by cross validation using only the training set , which is a symmetric window .

首先，对训练集采用交叉验证法确定最优窗口，它是非对称的。

Presented an efficient hybrid heuristic SGS -EM- PACOB algorithm for learning Bayesian network with missing values.

建立了具有数据缺失训练集下学习贝叶斯网的一种混合启发方法：SGS-EM-PACOB 算法。

The experiments on the TIDIGITS corpus show reduction on the error rate under mismatched condition of training and testing data .

在 TIDIGITS 数据库上的实验表明，该方法在训练集与测试集不匹配时能明显降低系统的误识率。

The training set and testing set were constructed to verify the effect of this model.

为了验证该方法的效果，构造了问题的训练集和测试集。

Survival rates in the training and validation set were very similar .

训练集与验证集患者的生存率非常相似。

Because the training assemble are tremendous and non-linear , a concept called sub-clusters reduced SVM is presented .

考虑到该训练集一般十分庞大且具有非线性可分的特性，提出子聚类约简的概念。

They can, however, be estimated from the training set .

但是这些都是可以通过训练集估计求得。

训练集

训练集