搜索资源列表
image-study
- 多示例学习是与监督学习、非监督学习和强化学习并列的第四类学习框架，目前已广泛应用于药物设计、图像搜索等领域,并已获得很好的效果。在多示例学习中，训练样本是由多个示例组成的包，包是有概念标记的，但示例本身却没有概念标记，学习的目的是预测新包的类别。-Multi-instance learning and supervised learning, unsupervised learning and reinforcement learning tied for the fourth-class le
m7_7
- 单神经元PID控制，基于有监督无监督以及改进的学习算法。-Single neuron PID control based on supervised unsupervised and improved learning algorithm.
SKohonen
- 有监督SOM网络，克服了无监督SOM聚类不准确的问题-The supervised SOM network, to overcome the unsupervised SOM clustering inaccurate
2008302590209
- 该程序可以实现基于K均值算法对彩色遥感图像(如SPOT)进行非监督分类 可以输入分类类别数,程序自动生成分类后的遥感专题图-The program can be achieved based on the K-means algorithm unsupervised classification of color remote sensing image (SPOT), you can enter the number of the categories, the program autom
NLKPCA
- 这是外国人实现的非线性主成份分析，可下载相应的文章，可用来降维！-Applies the kernel method to unsupervised algorithms as for instance Principal Component Analysis. This gives a principled and efficient approach to nonlinear PCA
Introduction-to-Graphical-Model
- matlab语句实现图模型，多用于分析网络用户产品推荐及网络用户潜在社会关系分析模型的建立。-The goal of building systems that can adapt to their environments and learn from their experience has attracted researchers from many fields , including computer science, engineering, mathematics, ph
vca_compress
- A Fast Algorithm to Unmix Hyperspectral Data-This paper presents a new method for unsupervised endmember extraction from hyperspectral data
k_mean
- 在聚类分析中，K-均值聚类算法（k-means algorithm）是无监督分类中的一种基本方法，其也称为C-均值算法，其基本思想是：通过迭代的方法，逐次更新各聚类中心的值，直至得到最好的聚类结果。 -In cluster analysis, K-means clustering algorithm (k-means algorithm) is unsupervised classification is a basic method, which is also known as C
class_toolbox
- maltab分类工具箱，整合了各种经典算法，在这些算法的帮助下有助于设计分类方法实验。-The classification toolbox is a list of functions for supervised and unsupervised classification algorithms. These algorithms help design categorization methods for experimental as well as synthetic dat
FCMClust
- 模糊聚类分析作为无监督机器学习的主要技术之一，是用模糊理论对重要数据分析和建模的方法，建立了样本类属的不确定性描述，能比较客观地反映现实世界，它已经有效地应用在大规模数据分析、数据挖掘、矢量量化、图像分割、模式识别等领域，具有重要的理论与实际应用价值，随着应用的深入发展，模糊聚类算法的研究不断丰富-Unsupervised fuzzy clustering analysis as the main machine learning techniques is the use of fuzzy t
kmeans
- kmeans算法，最基本的聚类算法，用于完成无指导的聚类问题，空间时间复杂性不高。-kmeans algorithm, the basic clustering algorithm, for the completion of unsupervised clustering problem, space-time complexity is not high.
kmeans
- image classification algorithm : k-means clustering implementation is provided herewith, which is an unsupervised clustering method
sofm-Mine--discrimination
- 无导师学习神经网络的分类——矿井突水水源判别-Unsupervised learning neural network classification- mine water inrush discrimination
kmeans--FCM-SOM
- 无监督分类方法，包括kmeans，som和fcm，非常好用-Unsupervised classification methods, including kmeans, som and fcm, very easy to use
UDFS
- unsupervised local discriminative analysis each column is a data- unsupervised local discriminative analysis each column is a data
Wyner-Ziv-Video-Coding
- The manuscr ipt describes the design of a new codec WZVC, where SI generation performed on unsupervised learning of two motion fields.
No--nearning-neural-network
- 无监督神经网络利用matlab能够有效的实现图像化，还能得到最有结果-Unsupervised neural network using matlab can effectively realize the image of, but also get the most results
1-s2.0-S0020025512007785-main.pdf
- Unsupervised fuzzy-rough set-based dimensionality reduction
sofm
- A self-organizing map (SOM) or self-organizing feature map (SOFM) is a type of artificial neural network (ANN) that is trained using unsupervised learning to produce a low-dimensional (typically two-dimensional)
DeepNeuralNetwork20131115
- It provides deep learning tools of deep belief networks (DBNs).-Run testDNN to try! Each function includes descr iption. Please check it! It provides deep learning tools of deep belief networks (DBNs) of stacked restricted Boltzmann machines (RB