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Description: 一种新型的功能强大的svm处理系统,拥有多种处理数据的能力-a new powerful svm processing systems, multiple data-handling capacity
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Size: 2725888 |
Author: 于林 |
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Description: 与spider配套的代码说明,目前只有在国外网站才能找到-spider with matching code that only the overseas sites can be found
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Size: 2485248 |
Author: 于林 |
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Description: Spider是很重要的SVM的工具包，非常实用，欢迎大家下载，S pider是很重要的SVM的工具包，非常实用，欢迎大家下载-it is great！it is great！it is great！it is great！it is great！it is great！it is great！it is great！it is great！
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Size: 10431488 |
Author: 朱涛 |
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Description: Multi-class Coding (adapted from from LS-SVM for SPIDER). Encode (code_MOC, code_ECOC, code_OneVsAll, code_OneVsOns) and decode (codedist_hamming, codedist_bay) a multi-class classification task into multiple binary classifiers.
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Size: 11264 |
Author: auksas |
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Description: matlab机器学习最新的工具箱，包含多种学习算法如kmean、adaboost、svm等-the latest machine learning matlab toolbox contains a variety of learning algorithms such as kmean, adaboost, svm, etc.
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Size: 5677056 |
Author: 朱建清 |
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Description: 机器学习matlab源代码，包括多分类SVM，模式识别，特征选择，回归等算法。-The spider is intended to be a complete object orientated environment for machine learning in Matlab. Aside from easy use of base learning algorithms, algorithms can be plugged together and can be compared with, e.g model selection, statistical tests and visual plots.
Core library objects
wilcoxon
Wilcoxon object- significance test of results
joint_kernel
Joint kernel object- for calculating inner products in joint feature spaces
joint_data
Joint_data object
corrt_test
corrected resampled t-test object- significance test of results
Unsupervised objects
spectral
Spectral clustering
ppca
Probabilistic Principal Components Analysis
nmf
Non-negative Matrix Factorization object
mrank
Manifold Ranking
Density Estimation objects
indep
Feature selection by independent density estimation
Feature Selection objects
r2w2_sel
Feature scaling/selection via SVMs and r^2/w^2 bound.
nfe
Non-Linear Feature Elimination
mutin
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Size: 212992 |
Author: 刘阳 |
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Description: 机器学习和模式识别工具包spider。内容很丰富。包含svm 决策树（C45,J48）、svm、knn、adaboost、bagging、hmm（隐马尔科夫模型）、随机树（random forest）等-Machine learning and pattern recognition toolkit spider. Very rich in contents. Tree contains svm (C45, J48), svm, knn, adaboost, bagging, hmm (hidden Markov model), random trees (random forest), etc.
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Size: 4979712 |
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