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原创 Neural Networks for Applied Sciences and Engineering--Chapter 5
Chapter 5 Implementation of Neural Network Models for Extracting Reliable Patterns from Datathe full article:http://note.youdao.com/noteshare?id=0627e2a45e34c2c4ae29bd04fa1af0d15.1 Introduction an
2017-01-29 21:11:46 310
原创 Neural Networks for Applied Sciences and Engineering--Chapter 4
Chapter 4 Learning of Nonlinear Patterns by Neural Networksthe complete article:http://note.youdao.com/noteshare?id=12d07d687a422d41b17375c614eda3624.1 Introduction and Overviewfirst-order error
2017-01-28 19:12:00 307
原创 Neural Networks for Applied Sciences and Engineering--Chapter 3
Chapter 3 Neural Networks for Nonlinear Pattern Recognition3.1 Overview and Introduction3.1.1 Multilayer PerceptronFor simple linear problems,hidden neurons are not required.3.2 Nonlinear
2017-01-23 16:22:46 322
原创 Neural Networks for Applied Sciences and Engineering--Chapter 2
Chapter 2 Fundamentals of Neural Networks and Models for Linear Data AnalysisThe full article:http://note.youdao.com/noteshare?id=909ec7e9da92bccc62de17a2feb04a402.5 Neuron Models and Learning S
2017-01-17 15:10:12 231
原创 the summary of sklearn.covariance
sklearn.covariance has three categories:EmpiricalCovariance and so on,Shrunkage,GraphLasso.EmpiricalCovariance:Maximum likelihood covariance estimator.If sample dataset has noisy data,we use MinCo
2017-01-03 10:00:48 470
原创 sklearn.covariance.ShrunkCovariance
from sklearn.covariance import ShrunkCovariancewords from wedia:Shrinkage estimation[edit]If the sample size n is small and the number of considered variables p is large, the above e
2016-12-09 18:26:12 399
原创 sklearn.covariance.MinCovDet
from sklearn.covariance import MinCovDetMCD Algorithm:https://wis.kuleuven.be/stat/robust/papers/2010/wire-mcd.pdf
2016-12-09 18:09:28 539
原创 sklearn.covariance.EllipticEnvelope
from sklearn.covariane import EllipticENvelopeAn object for detecting outliers in a Gaussian distributed dataset.the key to the question is the algorithm for the minimum covariance determinant est
2016-12-07 10:43:34 1932
原创 sklearn.covariance.GraphLasso
sklearn.covariance.GraphLassoclass sklearn.covariance.GraphLasso(alpha=0.01, mode='cd', tol=0.0001, enet_tol=0.0001, max_iter=100, verbose=False, assume_centered=False)[source]Sparse inverse c
2016-12-06 14:26:39 970
原创 sklearn.covariance.EmpiricalCovariance
from sklearn.covariance import EmpiricalCovarianceIs since the data set assumed to be drawn from Gaussian distribution ,empirical covariance is considered as the maximum likelihood covariance estima
2016-12-05 10:30:34 1172
原创 sklearn.cluster.Minibatch
Algorithm:http://www.eecs.tufts.edu/~dsculley/papers/fastkmeans.pdfThe motivation behind this method is that mini-batches tend to have lower stochastic noise than individual examples in
2016-12-02 13:37:25 673
原创 sparse data clustering with infinite-norm
def distance(X,v,tol): l = abs(X-v).apply(lambda x:sorted(x),axis=1) l = l.iloc[:,int(np.floor(X.shape[1]*tol))] return l def cluster_l1(df,threshold=0.05,tol=0.9,iternum=20,rnum
2016-11-30 16:32:56 229
原创 skearn.cluster.AffiinityPropagation
AP algorithm:http://blog.csdn.net/lixi__liu/article/details/48470173http://wenku.baidu.com/link?url=wthd1z0wj8qgunjxd3S-jgIpefnx-LgS5vCsvsl33RASsoUHjstIIfMwSWtb223EUb6HG8hLiEpwGAw8o4o0JkNvV-3CFS7C
2016-11-29 15:47:20 572
原创 sklearn.cluster.KMeans
#sklearn.cluster.KMeans#by muzhen'''Algorithm:initialize k centroidsfor sample in full samples: calculate the distance between sample and each centroids by using distance function,\
2016-11-23 10:38:36 1320
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