搜索资源列表
TextClassification_wbfl_sn
- 整个实验是在Windows环境下使用delphi完成的。选取了600篇文档，数据集共分教育，商业与经济，计算机与因特网，娱乐与休闲，自然科学5个类别， 教育类包括31篇文档， 商业与经济类有93篇文档， 计算机与因特网102篇文档， 娱乐与休闲166篇文档， 自然科学有208篇文档。 目录“dataset”：RawText中的文本分词后保存在dataset目录。 数据表“WordsTable”：保存dataset中所有文本的倒排文档。 其中“目录
lasvm-source-1.0.tar
- an approximate SVM solver, useful for very large dataset.
selfAffinity
- AP是在数据点的相似度矩阵的基础上进行聚类.对于规模很大的数据集,AP算法是一种快速、有效的聚类方法,这是其他传统的聚类算法所不能及的,-A semi-supervised clustering method based on affinity propagation (AP) algorithm is proposed in this paper. AP takes as input measures of similarity between pairs of data points. AP
NeuralNetwork
- Neural Network Application. Iris dataset and Wine dataset.
CIProject
- Computational Intelligence IRIS dataset Classification
popular-UCI-datasets
- 一些非常有用的数据集，适合我们从事机器学习的人使用，matlab下的mat格式和excel格式，包括注明的iris，糖尿病等数据集-some useful datasers for machine learning learners,such as diabeters,iris and so on
gridsearch
- 这是一个libsvm grid的改进,除了可以搜索分类中的C和gamma,还可以搜索小的整数.-This file is a slight modification of grid.py of libsvm. In addition to parameters C, gamma in classification, it searches for epsilon as well. Usage: grid.py [-log2c begin,end,step] [-log2g begin
datamining
- 以microsoft.com网站的一组处理后的web日志为数据（ftp://ftp.ics.uci.edu/pub/machine-learning-databases/anonymous/），利用并根据实际情况改进了聚类分析基于划分的方法类中最基本的Kmeans和Kmedoids方法，对下载数据集的一个采样(5000samples,294 attributes per sample)进行了简单的聚类分析，以期望找出有用的用户访问模式。 -web datamining with datase
classbaseattributetimeclassification
- In this paper, we present two novel class-based weighting methods for the Euclidean nearest neighbor algorithm and compare them with global weighting methods considering empirical results on a widely accepted time series classification benchm
MNIST-handwritten-digits
- 手写数字识别数据集，MNIST，包括原始数据集的所有样本，以及抽取的2000个样本的子集，.mat格式。美国著名数据集NIST的子集，模式识别常用实验数据集-handwritten digits recognition ,dataset, MNIST from NIST, .mat file,
mnist_all
- USPS手写字体数据集，声明：本源程序由网络搜集整理，不承担技术及版权问题!-USPS handwriting data set, the statement: This source collected by the network, does not bear the technical and copyright issues!
Unbiased-Look-at-dataset-Bias
- 这是一篇关于科研中如何选择数据测试集的文章，文章颠覆性的说明了我们在大多数实验中所谓的算法通用性，其实都在使用倾向我们结论的数据，而真正适合“所有”算法测试的数据集并没有得到验证。-This is an article about how to choose the scientific research data set of tests of the article, the article subversive to explain our in most of the so-called
datasets
- dataset in data mining and genetic algorithm-dataset in data mining and genetic algorithm
kddcup.data
- kddcup99数据集，ids测试数据集，很经典的-kddcup99 dataset ids set of test data, it is classic
wave1
- Sample frames from the Weizmann dataset. Summary: In this project, a new class of action recognition algorithms has been developed with performance
PMF
- Probabilistic Matrix Factorization 算法 用VS2010 C++实现，用于协同过滤。performs well on the large, sparse, and very imbalanced Netflix dataset。-we present the Probabilistic Matrix Factorization (PMF) model which scales linearly with the number of observ
pvm_code
- PVM is a fast supvervised leanring algorithm who combine dimensioin reduction and neural network training. I have prepared the code (including six algorithms KPVM, EL M/SVD, BP/SVD and BPVM, and one dataset "Face") and put them in one zip file "pvm
uspsFisher
- 用Fisher算法对usps数据集进行分类，对每个部分都有很好的说明，对画图也有详细说明-USPS dataset using Fisher algorithm classification, each part has a good descr iption of the drawing there are described in detail
uspsMSE
- 用MSE算法对usps数据集进行分类，对每个部分都有很好的说明，对画图也有详细说明-USPS dataset using MSE algorithm classification, each part has a good descr iption of the drawing there are described in detail
SceneTextCNN_demo.tar
- 端至端卷积神经网络的文字识别,代码演示包. 它包含我们的论文中使用的所有主要组成部分: kmeans无监督特征学习 + 卷积神经网络(CNN)-This is a demo package of the code we used for our paper, "End-to-End Text Recognition with Convolutional Neural Networks", T. Wang, D. Wu, A. Coates, A. Ng, in ICPR 2012.