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matrix matrices, and the column represents the feature, where the percentage represents the variance ratio of the number of features required before taking the default to 0.9" "defPCA (datamat,percentage=0.9): #averaging for each column, because the mean value is subtracted from the calculation of the covarianceMeanvals=mean (datamat,axis=0) meanremoved=datamat-meanvals#CoV () Calculating varianceCovmat=cov (meanremoved,rowvar=0)#using the Eig () method in the module linalg for finding eigen
Brief introduction In recent years, because of the cloud platform, large data, high-performance computing, machine learning and other areas of progress, artificial intelligence also fire up. Face recognition, speech recognition and other related functions have been proposed, but can form products and large-scale use of small. Because it is difficult for non-profe
http://mp.weixin.qq.com/s?__biz=MjAzNzMzNTkyMQ==mid=211346099idx=1sn= 41d9c9761e729ed57a89ae2aaaa66bb1scene=0#rdAbout the specific concept of machine learning and introduction, there are a lot of this information, if you are interested, you can go to see, here I will not repeat. In short, the machine
Gan Introduction Generativeadversarial Nets The idea of generating a confrontation network was put forward in 2014, in the original paper, the author uses game theory to explain the thought behind the Gan frame. Each Gan frame contains a generative model G and a discriminant model D, the task of which is to determine whether a given image looks ' natural ', in other words, as if it were a machine-generated.
Recently TalkingData Open source The main role of Fregata,fregata is to speed up the computing speed of machine learning based on spark, it is said that 1 billion * 1 billion level of data if cached in memory, the 1s clock can be completed, if not cached, 10 seconds to fix, If this is the case, it is a fortress, and the following are only translations, if there are incorrect welcome corrections Brief
reduction of the kernel dimension of tree-shaped structure3.1 Motive3.2 Introduction to the tree-shaped algorithm3.3 (residual) tree core dimensionality reduction3.4 Experimental Section3.5 ConclusionApplication of 4 nuclear dimensionality reduction in population counting4.1 Nuclear dimensionality reduction4.2 Multi-core learning5 ConclusionReference machine learning
-schonberger, and Kenneth CukierA Short but insightful manuscript that'll motivate you to rethink how we should face the explosive growth of data in the New century.Statistical Pattern Recognition (2nd/3rd Edition)Andrew R. Webb, and Keith D. CopseyA well written book on the pattern Recognition for beginners. It covers basic topics in this field, including discriminant analysis, decision Trees, feature selection, and clustering- -All is basic knowledg
This column (Machine learning) includes single parameter linear regression, multiple parameter linear regression, Octave Tutorial, Logistic regression, regularization, neural network, machine learning system design, SVM (Support vector machines Support vector machine), clust
-julia Generalized linear model packages written by Glm-julia Online Learning Glmnet-gmlnet's Julia Packaging edition, suitable for lasso/elastic mesh models. clustering-basic functions of data clustering: K-means, Dp-means, etc. Support Vector machine under the Svm-julia. Kernel Density estimator under kernal density-julia dimensional
Building a Java development environmentDeveloping MyEclipse with development toolsBase Core: Javaseeeme Object-oriented API JVM.Java EE refers to Edition,java Enterprise Edition, which is used for enterprise-level development, including web development and many otherJavase refers to Java standard Edition,java, which is the development of generic Java programs, ca
, so the routing function needs to be turned on. echo 1 >/proc/sys/net/ipv4/ip_forward (7) Turn off firewall iptables-vnl View firewall policy centos6chkconfig iptables off setting boot does not turn on firewall servcie Iptables Stop Firewall centos7systemctl disable FIREWALLD settings boot does not turn on firewall systemctl stop FIREWALLD shut down Firewall (8) test test with ping command, each segment can pin G-Pass. A->vmnet12:ping 6.2.0.201a->vmnet13:ping 6.3.0.100 Four, the routing protoco
What is integrated learning, in a word, heads the top of Zhuge Liang. In the performance of classification, multiple weak classifier combinations become strong classifiers. In a word, it is assumed that there are some differences between the weak classifiers (such as different algorithms, or different parameters of the same algorithm), which results in different classification decision boundaries, which means that they make different mistakes when ma
deep understanding of machine learning: Learning Notes from principles to algorithms-1th week 02 easy to get started Deep understanding of machine learning from principle to algorithmic learning notes-1th week 02 Easy to get star
The motive and application of machine learningTools: Need genuine: Matlab, free: Octavedefinition (Arthur Samuel 1959):The research field that gives the computer learning ability without directly programming the problem.Example: Arthur's chess procedure, calculates the probability of winning each step, and eventually defeats the program author himself. (Feel the idea of using decision trees)definition 2(Tom
learning Adventure JourneysklearnProvides a lot of machine learning algorithm implementation, in the learning process I can not do a full study and coverage. After many searches, I found the Youtube sentdex released video "machine Learn
Source: From Machine learningThis paper first introduces the trend of Internet community and machine learning Daniel, and the application of machine learning, then introduces the machine learn
Source: https://www.cnblogs.com/jianxinzhou/p/4083921.html1. The problem of overfitting (1) Let's look at the example of predicting house price. We will first perform linear regression on the data, that is, the first graph on the left. If we do this, we can obtain such a straight line that fits the data, but in fact this is not a good model. Let's look at the data. Obviously, as the area of the house increases, the changes in the housing price tend to be stable, or the more you move to the right
See "Those years we chased the Wrox boutique red leather computer book" prize eventDownload the probation pdf of the Visual c++2013 Primer Classic (7th edition) and start learning. The reader of this bookThis book is intended for anyone who wants to learn how to use Visual C + + to write C + + running under Microsoft Windows operating systemThe reader of the application. Reading this book requires no prior
automated Systems developed with automated Python (using Python to build a Machine Learning system) Building automated Machine Learning automated Systems developed with automated Python, developed 2nd automated Edition (build a Machine
What are two models? We have come to these two concepts from a few words:1, machine learning is divided into supervised machine learning and unsupervised machine learning;2, supervised machine
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