查询词典 classifiers

The thesis presents a novel Borda count method that integrates correlative information between multi-classifiers.

在以往图像检索技术的基础上，提出了新的加入多个分类器相关信息的Borda计数的特征融合图像检索方法。

Secondly, aiming at enhancing the ability of color classification for the color panoramic image, the dissertation proposed a combined color space CLUT (Color Look-Up Table) color classification method based on the linear classifiers.

论文分析了该系统的设计原则，介绍了该系统各主要组成部分的特点、主要参数的测量方法，确定了彩色全向视觉系统的距离测量有效范围。

The central problem of combination principle is how to solve the collision when component classifiers disagree.

组合原则的中心问题是当参与组合的各分类器出现不一致的情况下，如何解决这种冲突。

Through an appropriate combination principle, a classifier with better performance can be constructed from these component classifiers.

通过某种合适的组合原则，由以上的几个分类器能获得一个性能较好的组合分类器。

Its application to numeral recognition shows that the improved Bayes principle made the combination of multiple classifiers achieve good performance of high recognition rate and high reliability.

在数字识别中的应用结果表明，改进的贝叶斯规则可以使多分类器的组合结果识别率和置信度得到明显提高。

In this paper,through extracting the feature of the off-line handwritten numeric characters based on the feature complementary,a method of integrated multi-classifiers of complementary based on the degree of confidence is proposed,witch includes the technology of the least distance classifier,the tree classifier as well as the BP network classifier.

通过对离线手写数字的特征提取，从特征互补的角度出发，采用了最小距离分类器、树分类器和BP网络分类器进行多分类器互补集成，提出了基于置信度的多分类器互补集成方法。

In order to make good use of the advanced technology of data mining, two kinds of classifiers (C4.5 decision tree and support vector machine, SVM) from data mining are improved.

3为了有效地利用数据挖掘的先进技术，对数据挖掘中两种分类方法C4.5决策树以及SVM进行了改进。

Among used machine learning methods, the gradient descent method is widely used to train various classifiers, such as Back-propagation neural network and linear text classifier. However, the gradient descent method is easily trapped into a local minimum and slowly converges. Thus, this study presents a gradient forecasting search method based on prediction methods to enhance the performance of the gradient descent method in order to develop a more efficient and precise machine learning method for Web mining.However, a prediction method with few sample data items and precise forecasting ability is a key issue to the gradient forecasting search method. Applying statistic-based prediction methods to implement GFSM is unsuitable because they require a large number of data items to model a prediction model. In the contrast with statistic-based prediction methods, GM(1,1) grey prediction model does not need a large number of data items to build a prediction model, and it has low computational load. However, the original GM(1,1) grey prediction model uses a mathematical hypothesis and approximation to transform a continuous differential equation into a discrete difference equation in order to model a forecasting model.

其中梯度法是一个最常被使用来实现机器学习的方法之一，然而梯度法具有学习速度慢以及容易陷入局部最佳解的缺点，因此，本研究提出一个梯度预测搜寻法则(gradient forecasting search method， GFSM)来改善传统梯度法的缺点，用来提升一些以梯度学习法则为基础的分类器在资讯探勘上的效率与正确性；而一个所需资料量少、计算复杂度低且精确的预测模型是梯度预测搜寻法能否有效进行最佳解搜寻之关键因素，传统统计为基础之预测方法的缺点是需要较大量的数据进行预测，因此计算复杂度高，灰色预测模型具有建模资料少且计算复杂度低等优点，然而灰色预测理论以连续之微分方程式为基础，并且透过一些数学上的假设与近似，将连续之微分方程式转换成离散之差分方程式来对离散型资料进行建模及预测，这样的作法不尽合理，且缺乏数学理论上的完备性，因为在转换过程中已经造成建模上的误差，且建模过程仅考虑相邻的两个资料点关系，无法正确反应数列未来的变化趋势。

In the selection of the subcategory of verbs and material classifiers, but disyllabic adjectives are free at their selection.

通过单双音节形容词的选择性考察，说明二者在语用上并不完全等价，单音节形容词往往受到较多的限制。

In this paper we propose a novel evidential approach to combining decisions given by multiple classifiers.

本文提出一种新颖的方法结合证据决定给予多分类。

We will see more and more activist government policies that distinguish economic activities according to the nationality of the actors.

我们将看到越来越多激进的政府政策，这些政策根据企业的国籍来区分经济活动。

If we can prove the independence of an axiomatic system, then we can guarantee the conciseness of this system, ie.

如果能够证明某个一阶谓词系统的独立性，那么就能够保证该系统的建立是精炼的，即没有任何一条公理或推理规则是多余的。