该类学习机也是在少训练样本集上构造的。
The reduced training set is used to form the learning machines.
把试验获取的数据整理分为训练样本集和测试样本集。
The experimental data obtained were divided into training set and testing data.
采用生产现场数据制做了预测模型的训练样本集和测试样本集。
The training sample sets and test sample sets for the ANN model were prepared from the real production of the continuous casting production.
在非线性多功能传感器的信号重构过程中，训练样本集不可避免地夹杂粗差数据。
Training sample set inevitably contains gross error in input signal reconstruction of nonlinear multifunctional sensor.
用训练样本集对网络训练后，检验样本的预测结果与实际值最大误差为0.97%。
The model was trained with training sample aggregation. The maximum error between the forecasted and real value was 0.97%.
基于原训练样本集和新增训练样本集在增量训练中地位等同，提出了一种新的SVM增量学习算法。
Based on the equivalence between the original training set and the newly added training set, a new algorithm for SVM-based incremental learning was proposed.
分析了训练样本集的大小对模型误差的影响，指出在训练样本不少于14个的情况下，模型具有较高的预测精度。
The effect of training set size on the error of neural network model is analyzed. The results show that the model has reasonable accuracy when the training set size is not less than 14.
本文主要研究由给定的训练样本集，如何选择最优小波包基，从被识别或分类的信号中提取具有最大可分性的特征。
This paper is mainly concerned with extracting effective features from the recognized or classified signals by selecting wavelet packet basis via given training sample sets.
在MATLAB环境下对所研究的图像重建用RBF神经网络进行训练，并通过有限元法获得训练所需要的训练样本集。
The RBF neural networks for image reconstruction were trained in MATLAB environment. The training samples were obtained by using finite element method.
在MATLAB环境下对所研究的图像重建用RBF神经网络进行训练，并通过有限元法获得训练所需要的训练样本集。
The RBF neural networks for image reconstruction were trained in MATLAB environment. The training samples were obtained by using finite element method.
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