learning tree itil foundation

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Introduction to ITIL & CMDB Learning

HP, IBM, BMC, CA, Peregrine and so on, summarizes the best practice experience of IT services and forms a process-based approach to standardize IT service levels. The goal of ITIL is to identify the programs that are really needed for it customers, which are necessary to deliver high-quality, best-fit services, at an acceptable cost. What needs to be managed in IT infrastructure. There are hardware, software, programs, documents, people.

"Machine Learning Algorithm Foundation + Combat series" Decision tree algorithm

General feature selection are the information gain or the information gain ratio we are taking.Information gain:First we give the definition of entropy: The uncertainty of the random variable represented by entropy.Set \ (x\) is a discrete random variable with a finite number of values, with a probability distribution of:\[p (X=x_{i}) =p_{i}, i =,..., n\]The entropy of the random variable is defined as: \[H (X) =-\sum_{i=1}^{n}p_{i}logp_{i}\]Normally, the logarithm in the equation is based on 2

Machine Learning Classic algorithm and Python implementation--cart classification decision tree, regression tree and model tree

handled in the same way as C4.5. To avoid overfitting (Overfitting), the cart decision tree needs pruning. The prediction process is also very simple, according to the resulting decision tree model, the extension of matching eigenvalues to the last leaf node is the category of prediction.When you create a regression tree, the values of the observations are conti

Starting from the Zero Foundation Learning CCNA learning experience Vomiting Blood summary

, port conversion of different applications, how to achieve the application of internal and external NAT, to achieve load balancing or shunt security policies.14. WAN Technology and PPP protocolRemote access to Wideband technology, PPP protocol LCP and NCP functions, LCP PAP and CHAP authentication methods, etc.15. Frame Relay and VTP technologyThe Frame Relay environment constructs the method, the GNS simulator uses the technique, complements the VTP technology, 3 big mode difference and the fu

Statistical Learning Method One: Foundation

(×)is called a build method because the model represents the build relationship of the output y produced by the given input x(2) Typical generation model: naive Bayesian and Hidden Markov models(3) Advantages: can restore the joint probability distribution P (x, y), learning convergence faster, there are hidden variables, you can still use the generation method to learn2) Discriminant method(1) Direct learning

PHP Beginners Learning Method _php Foundation

powerful library of functions, to learn it, you must spend a lot of time to remember, good memory can make learning to achieve a multiplier effect. 2. Mathematics and Logical Thinking This is certainly not an absolute effect, because look at the complexity of the development project. Small projects do not require much mathematical and logical thinking, but it is important to develop projects that are similar to finance or a large number of operat

[Method Summary] How to get started a new field/technology? -"Learning by using the knowledge tree to promote learning"

fulfilling.) )After that, I used this "use to learn" method to learn new domain technology. Including the recent learning of blockchain technology is also the case, I first on the whole blockchain has a general understanding of the inside some of the proper terminology, and the use of technology. Then there is a basic understanding of blockchain development. After setting up this framework, I have to conquer the core principles. Finally, prepare to d

2017-2018-2 20179204 "Network attack and Defense practice" First week learning summary of the Linux Foundation

Log System Common logs are typically stored in/var/log: You can roughly divide the logs into two categories based on the service object: System log, Application log. System log is mainly for the system built-in program or system kernel such as log information such as Alternatives.log, btmp and so on, the application log is the third-party application of our installed log such as TOMCAT7, apache2 and so on. references Getting Started with Linux Basics (new version)

Python Learning (23)-The jquery of the front-end Foundation

HTML code for the element with the ID value. html()This is the method in jquery. equivalent to document.getElementById("i1").innerHTML; :Although jQuery对象 it is DOM对象 produced after packaging, but jQuery对象 can not be used in DOM对象 any way, the DOM对象 same way can not be used in jQuery the method.A convention, when declaring a jquery object variable, precede the variable name with $:var $variable = jquery pair like var variable = dom object $variable[0] // jquery objects Turn into DOM objectsT

Data Structure Learning series Binary search tree

fast search and Insert, as well as rank,Select,Delete, and range lookups. But in reality,worst-case is not impossible to happen, such as the client inserting key in full order or in reverse . The performance of the algorithm degrades to N and becomes a linear lookup, so this possibility is why we are looking for better algorithms and data structures. Binary search Tree application is not many, because it is the worst time with the linear table, most

Machine Learning -- gradient boost demo-tree (& treelink)

From: http://www.cnblogs.com/joneswood/archive/2012/03/04/2379615.html 1. What is treelink? Treelink is the internal name of Alibaba Group. Its Academic name is gbdt (gradient boosting demo-tree, gradient escalation Decision Tree ). Gbdt is one of the two basic forms of algorithms related to "model combination + Decision Tree", and the other is random forest (ran

Machine Learning Foundation 5--document similarity retrieval and measurement algorithm

64 documents, the word "the" appears 1000 times in 63 documents, and Messi appears 5 times in 3 documents. The bottom is 2.The:log (64/1+63) = 0Messi:log (64/1+3) = 4Then TF * IDFthe:1000 * 0 = 0Messi:4 * 5 = 20We need a function:Defines a distance that is used to measure similarity.1. We can calculate the similarity of this article and other articles, and return an optimal result.2. We can calculate the similarity between this article and other articles, and return the K most relevant results

Tree-like array learning

production two times high 1, is through the c[0110] indirect influence, but, c[ 0100] But can jump one level to produce a high 1.Perhaps the above said you are more around, then you only need to pay attention to: C of the constituent nature (in fact, the group nature) determines c[0011] only directly affect the c[0100], and c[0100] only directly affect [1000], and the relationship between the following table is also must be K +=lowbit (k). At this point we are writing the code with the new main

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