incremental learning的例句大全

A weighted class incremental learning algorithm is presented, which improves the CIL algorithm. The algorithm adds the weighs of class to training samples.

提出了一种加权类增量学习算法，该算法是对CIL算法的改进，通过加入类权值，解决了因两类训练样本不平衡而造成的小类别分类精度较低的问题。

When tagging a large number of categories with high price of the sample, combined with the incremental learning theory is an effective way to solve the problem.

当获得大量带有类别标注的样本代价较高时，与增量学习理论结合是解决问题的有效途径。

Multi-class Incremental Learning Based on Support Vector Machines

基于支持向量机的多分类增量学习算法

Model experiments show that, the financial distress prediction model based on the incremental learning system is stable and adaptable. Incremental prediction model outperforms other models, which is an effective financial distress prediction method.

财务数据实验表明，基于增量学习系统的财务危机预警模型兼具稳定性和适应性，模型预测性能优于滑动时间窗口模型，是一种有效的财务危机预警建模方法。

Based on the out-of-sample framework and the graph embedding framework, the thesis presents a more general common framework for manifold learning. The new framework embodies graph construction, tensor learning, incremental learning and supervised learning.

提出新的流形学习统一框架在样本泛化与图嵌理论的基础上，提出了更一般的流形学习统一框架，这一框架包含了图的建立、张量学习、增量学习和有监督学习。

research on incremental learning algorithm with multiple support vector machine classifiers

基于多支持向量机分类器的增量学习算法研究

As an incremental learning system, Case-based reasoning ( CBR) makes the knowledge and rule obtainment bottleneck easy by learning from case, thus it has increasingly become a hotspot in the area of artificial intelligent.

基于事例的推理（CBR）作为一种增量式的学习方法，规避了传统人工智能在知识获取上的瓶颈问题，逐渐引起人工智能领域研究者的关注。

The incremental learning algorithm in hybrid learning model HLM

混合型学习模型HLM中的增量学习算法

An incremental learning algorithm using multiple support vector machines ( SVMs) is proposed.

给出了使用多支持向量机进行增量学习的算法。

Besides, based on hyper sphere SVMs, a new class incremental learning algorithm is presented.

同时，提出了一种新的类增量学习算法，该算法利用超球支持向量机进行分类。

Based on this cognition, corporations realize incremental and radical innovation by conditioning, modeling, adaptive creative and meta learning.

在这个基础上，企业通过条件学习、模式学习、适应学习、创造学习与元学习，实现企业渐近创新和重大创新。

an incremental hybrid learning algorithm with noise resistance ability

一种具有抗噪音能力的增量式混合学习算法

learning needs to be grounded in experience and exposure, and encourage incremental development.

学习需要植根于经验和接触，并鼓励增量发展。

Accordingly, the incremental random forest is applied to visual tracking as core learning algorithm under particle filter framework. The classifier is updated by sequentially arrived samples during tracking process.

本文将上述增量随机森林作为鉴别型表观模型应用于视觉目标跟踪，在跟踪过程中提取新的正/负样本不断更新分类器。