搜索资源列表
CVPR_guider
- 里面介绍了机器视觉的学习相关网站，由低到高，适合参考-Which introduced the study of machine vision-related sites, from low to high, suitable for reference
machinevision
- 国内机器视觉、图像处理行业分析，对研究生阶段学习这个行业的要求，希望这个方向的研究生-Domestic machine vision, image processing, industry analysis, stage of post-graduate study and the requirements of the industry, I hope in this direction a good look at the post-graduate
BP_Network
- 机器学习中的单层感知器学习算法，可自动实现两个向量的逻辑与运算。-Machine learning in single-layer perceptron learning algorithm, can be self-fulfilling logic of the two vectors and computing.
weka-src
- weka源代码 最全最新的 数据挖掘用机器学习实现。包含聚类 分类 关联规则 离群点监测。java平台-weka most up-to-date source of data mining using machine learning to achieve. Clustering association rules classification contains outliers monitoring. java platform
libsvm
- SVM代码库的vc实现，有涉及机器学习领域的人可以参考-SVM code base to achieve the vc, it involves the field of machine learning can refer to
fast-C-src-2.1.tar
- FAST 角点检测，很好很实用的代码，基于机器学习。感兴趣的可以下载参考一下。-FAST corner detection, good code is very practical, based on machine learning. Interested can download the reference.
1234
- uci机器学习数据库关于字符识别的源数据。是字符识别的研究的关键数据来源。包括手写字体和印刷体两类，手写的数字和印刷体的字母。-uci machine learning database on the source character recognition data. Character recognition research is the key source of data. Including two types of handwriting fonts, and print, han
Learning_OpenCV
- 一本相当好OpenCV教程,包括图像处理、计算机视觉和机器学习等-There is a very good tutorial of OpenCV. It includes image processing, computer vision and machine learning.
BParithmetic
- 机器学习。神经网络算法。 用c语言开发。-Machine learning. Neural network algorithm. Using c language.
75785
- 机器学习与数据挖掘方法和应用（经典）.pdf-Machine Learning and Data Mining Methods and Applications (Classic). Pdf. . . . . . . .
SVMcode
- 基于svm的机器学习文本分类方法，具有很好的借鉴意义-Svm-based machine learning text classification methods, with a good reference
proj2.release
- 机器学习-人脸识别，根据给定的学习样例，提取特征，生成分类。对测试的样例进行人脸方向的分类。需要在vs中进行开发。-Machine learning- face recognition, according to the given learning sample, extract features, generate classification. The test sample to face the direction of classification. Vs the need to d
DMES
- 支持基于可识别性的经验建模和数据挖掘。它由许多用于通用机器学习和粗糙集理论的例程组成-Support based on the experience of identification in the modeling and data mining. It is used by many general-purpose machine learning and routine composition of rough set theory
project_onto_simplex
- l1范数的投影源码,用于高维的机器学习问题-L1 projection source codes
SVMApplication
- 图像处理和模式识别领域的重要工具，支持向量机目前受到机器学习领域的广泛关注-SVM matlab program
libsvm-2.88-string
- SVM一个分类组件，用于分类的算法,和决策树等算法都是用于机器学习的算法-SVM
dgdgdgdgdgfdgdfgrelevance
- 基于支持向量机的相关反馈图像检索算法 相关反馈技术是近年来在图像检索中较为重要的 研究方法, 从机器学习的角度, 以支持向量机(SVM ) 为分类器, 提出了一种新的相关反馈方法-Support vector mach ine based relevance feedback algorithm in image retrieval
weka-src
- 开发环境：eclipse WEKA是一个数据挖掘工作平台，集合了大量能承担数据挖掘任务的机器学习算法，包括对数据进行预处理，分类，回归、聚类、关联规则以及在新的交互式界面上的可视化。 -Development environment: eclipse WEKA is a data mining work platform, a collection of a lot to take on the task of data mining machine learning algorithms,
machinelearninganddatamining
- “机器学习”是人工智能的核心研究领域之一， 其最初的研究动机是为了让计算机系统具有人的学习能力以便实现人工智能，因为众所周知，没有学习能力的系统很难被认为是具有智能的。“数据挖掘”和“知识发现”通常被相提并论，并在许多场合被认为是可以相互替代的术语。据库界提供的技术来管理海量数据。 因为机器学习和数据挖掘有密切的联系，受主编之邀，本文把它们放在一起做一个粗浅的介绍。-" Machine learning" is the core research areas of arti
multiboost-0.61.src.tar
- Adaboost实现，主要用于机器学习的多分类器聚合， 最终形成分类效果逐渐增强的分类器-Adaboost implementation, is mainly used for machine learning, multiple classifier aggregation, the final shape classification results show a gradual increase of the classifier