给出了使用多支持向量机进行增量学习的算法。
An incremental learning algorithm using multiple support vector machines (SVMs) is proposed.
提出了可将此改进算法应用到增量学习SVM中。
In addition, the application of the SOR-ASVM method to the incremental SVM is proposed.
提出了一种改进的基于KKT条件的增量学习算法。
Presents an improved incremental learning algorithm based on KKT conditions.
本文提出了基于增量学习神经模糊网络机动目标跟踪模型。
The scheme of tracking maneuvering target based on neural fuzzy network with increased leaning is proposed.
本算法具有速度快、增量学习、使用的支持向量少等显著优点。
This algorithm is fast, incremental learning, and it takes less support vectors!
文中基于块增量学习和逆学习过程，提出了自适应迭代回归算法。
This paper presents an adaptive and iterative support vector machine regression algorithm (CAISVR) based on chunking incremental learning and decremental learning procedures.
增量学习是一个主要特征，自然情报，如何将机器人模型增量学习？
Incremental Learning is one of major characteristics of natural intelligence, how shall robotics model Incremental Learning?
基于拉推策略的基本思想，该文提出了文本分类的增量学习模型ICCDP。
Based on DragPush strategy, the paper introduces a text classification incremental learning model, named ICCDP.
分布式入侵检测系统；人工神经网络；增量学习；融合学习；神经网络修剪。
Distribution Intrusion Detection System; Artificial Neural Networks; Incremental learning; Integrated learning; Neural network pruning.
本算法在保证分类准确度的同时，在增量学习问题上比传统的支持向量机有效。
This algorithm, in the incremental study question, is more effective than the traditional support vector machine, with assuring the classify accuracy.
增量学习是一种在巩固原有学习成果的基础上快速有效地获取新知识的学习模式。
Incremental learning mode is meaningful to efficiently acquire additional knowledge on the basis of original knowledge structure.
为解决该问题，本文采用了决策树增量学习法和神经网络完全学习相结合的方法。
In this paper, a new approach is set forth that integrating both decision tree incremental learning and neural network global learning. Through theory analysis, it's indicated th…
该方法采用增量学习的思想，对话题追踪任务中的自适应学习机制提出了新的算法。
This method adopts the idea of increment learning, and presents new algorithm to the adaptive learning mechanism in the task of topic tracking.
该方法采用增量学习的思想，对话题追踪任务中的自适应学习机制提出了新的算法。
Based on the idea of increment learning, the paper presents a new algorithm for the adaptive learning mechanism in the task of topic tracking.
本文提出并推导了特征分解的校正算法，并以此为基础，实现了增量学习的主成分分析方法。
In this paper, by developing a method for updating eigen decomposition, we proposed an incremental Principal Component Analysis.
该算法综合了决策树方法和贝叶斯方法的优点，既有良好的可解释性，又有良好的增量学习能力。
The new algorithm combines the merit of decision tree induction method and naive Bayesian method. It retains the good interpretability of decision tree and has good incremental learning ability.
该算法通过在增量学习中逐步积累样本的空间分布知识，使得对样本进行有选择地遗忘成为可能。
This algorithm accumulates distribution knowledge of the training sample while the incremental training is proceeded, and thus makes it possible to discard samples optimally.
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.
为了将一般增量学习算法扩展到并行计算环境中，提出一种基于多支持向量机分类器的增量学习算法。
In order to extend common incremental learning algorithms into a parallel computation setting, an incremental learning algorithm with multiple support vector machine classifiers is proposed.
该算法将主动式学习、有偏分类和增量学习结合起来，对相关反馈过程中的小样本有偏学习问题进行建模。
The algorithm combines active learning, biased classification and incremental learning to model the small sample biased learning problem in relevance feedback process.
他们应该考虑一些敏捷(Agile)开发方法，例如极限编程(XP)，这种开发方法采用一种增量学习及开发方法。
Instead, consider adopting some of the new Agile development methods, such as Extreme Programming (XP), that foster this kind of incremental learning and development.
文中针对该算法这两个最主要的缺陷，提出增量学习概念，引入损失幅度参数，改进和完善朴素贝叶斯分类算法。
Then in allusion to these two important factors, a concept of incremental learning and a loss extent parameter are put forward in this paper, and Native Bayesian Classification.
摘要：在增量学习过程中，随着训练集规模的增大，支持向量机的学习过程需要占用大量内存，寻优速度非常缓慢。
Absrtact: During the incremental learning, with the increase of the training set, it is very costly to process these data in terms of time and memory consumption.
本文研究了基于增量决策树的主动学习方法，其实就是将增量学习和主动学习两种方法进行有效地结合，从而同时发挥二者的优势。
In this paper, we study the active learning method based on the incremental decision tree through which combines the merits from the incremental learning and the active learning.
实验结果表明IBN-M算法在数据缺失下贝叶斯网络的增量学习中确实能够学出相对精确的网络模型，该算法也是对贝叶斯网络增量学习方面的一个必要的补充。
The experiments show that IBN-M algorithm can learn comparatively accurate network from the extremely large dataset. IBN-M is an interesting improvement for incremental learning Bayesian Network.
针对这些问题，基于最小化学习误差的增量思想，该文将学习型矢量量化（LVQ）和生长型神经气（GNG）结合起来提出一种新的增量学习型矢量量化方法，并将其应用到文本分类中。
To solve these problems, based on minimizing the increment of learning errors and combining LVQ and GNG, the authors propose a new growing LVQ method and apply it to text classification.
增量算法是提高学习效率的一个重要算法之一。
Incremental algorithm is one of the major algorithms for raising learning efficiency.
提出了一种快速、增量式的学习算法。
提出了一种新的基于壳向量的增量式支持向量机快速学习算法。
A new geometric fast incremental learning algorithm for support vector machines (SVM) was proposed.
提出了一种新的基于壳向量的增量式支持向量机快速学习算法。
A new geometric fast incremental learning algorithm for support vector machines (SVM) was proposed.
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