Description: 最大最小值估计，适合学习统计理论和模糊方面的结合应用，尤其是在模式识别方面的分类。-largest minimum estimate for statistical learning theory and fuzzy combination of the application, especially in regard to the classification of pattern recognition. Platform: |
Size: 4096 |
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Description: 用于人脸识别的模糊独立成分分析+主成分分析，用模糊支持向量机进行的分类。-Fuzzy Face Recognition for independent component analysis+ principal component analysis, using fuzzy support vector machine classification. Platform: |
Size: 2030592 |
Author:戴欢 |
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Description: 基于MATLAB的模糊模式识别在癌细胞识别中的应用-Based on the MATLAB language Use computer fuzzy pattern recognition to determine the classification of cancer cells Platform: |
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Author:薛正 |
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Description: 模式识别与智能计算的一个基于matlab运行的识别分类软件，聚集了模糊聚类，SVM，神经网络等各种流行的分类算法于一体，便于比较测试数据在不同分类算法下的分类效果-Pattern Recognition and Intelligent Identification and Classification of the calculation to run a matlab software, gathered a variety of popular fuzzy clustering, SVM, neural network classification algorithm in one easy to compare test data classification results in different classification algorithms Platform: |
Size: 16740352 |
Author:胡 |
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Description: 数据挖掘(Data Mining)阶段首先要确定挖掘的任务或目的。数据挖掘的目的就是得出隐藏在数据中的有价值的信息。数据挖掘是一门涉及面很广的交叉学科，包括器学习、数理统计、神经网络、数据库、模式识别、粗糙集、模糊数学等相关技术。它也常被称为“知识发现”。知识发现(KDD)被认为是从数据中发现有用知识的整个过程。数据挖掘被认为是KDD过程中的一个特定步骤，它用专门算法从数据中抽取模式(patter，如数据分类、聚类、关联规则发现或序列模式发现等。数据挖掘主要步骤是：数据准备、数据挖掘、结果的解释评估。-Data Mining (Data Mining) stage must first determine the mission or purpose of the excavation. The purpose of data mining is to draw valuable information hidden in the data. Data mining is an interdisciplinary involving a wide range, including control study, mathematical statistics, neural networks, databases, pattern recognition, rough sets, fuzzy mathematics and other related technologies. It is also often referred to as the " knowledge discovery" . Knowledge discovery (KDD) is that the whole process is to discover useful knowledge from data. Data mining is a particular step in the KDD process, with a special algorithm (patter, such as data classification, clustering, association rules discovery or sequential pattern discovery. Extracted from the data model and data mining major steps: data preparation, data mining, interpretation of the results evaluated. Platform: |
Size: 12288 |
Author:dlufl |
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