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Auto-Machine-Learning-<b>METHODs</b>-Sys

  • a Java toolkit for training, testing, and applying Bayesian Network Classifiers. Implemented classif

    a Java toolkit for training, testing, and applying Bayesian Network Classifiers. Implemented classifiers have been shown to perform well in a variety of artificial intelligence, machine learning, and data mining applications.

    標簽: Classifiers Implemented Bayesian applying

    上傳時間: 2015-09-11

    上傳用戶:ommshaggar

  • 上下文無關(guān)文法(Context-Free Grammar, CFG)是一個4元組G=(V, T, S, P)

    上下文無關(guān)文法(Context-Free Grammar, CFG)是一個4元組G=(V, T, S, P),其中,V和T是不相交的有限集,S∈V,P是一組有限的產(chǎn)生式規(guī)則集,形如A→α,其中A∈V,且α∈(V∪T)*。V的元素稱為非終結(jié)符,T的元素稱為終結(jié)符,S是一個特殊的非終結(jié)符,稱為文法開始符。 設(shè)G=(V, T, S, P)是一個CFG,則G產(chǎn)生的語言是所有可由G產(chǎn)生的字符串組成的集合,即L(G)={x∈T* | Sx}。一個語言L是上下文無關(guān)語言(Context-Free Language, CFL),當(dāng)且僅當(dāng)存在一個CFG G,使得L=L(G)。 *⇒ 例如,設(shè)文法G:S→AB A→aA|a B→bB|b 則L(G)={a^nb^m | n,m>=1} 其中非終結(jié)符都是大寫字母,開始符都是S,終結(jié)符都是小寫字母。

    標簽: Context-Free Grammar CFG

    上傳時間: 2013-12-10

    上傳用戶:gaojiao1999

  • 一:需求分析 1. 問題描述 魔王總是使用自己的一種非常精練而抽象的語言講話,沒人能聽懂,但他的語言是可逐步解釋成人能聽懂的語言,因為他的語言是由以下兩種形式的規(guī)則由人的語言逐步抽象上去的: -

    一:需求分析 1. 問題描述 魔王總是使用自己的一種非常精練而抽象的語言講話,沒人能聽懂,但他的語言是可逐步解釋成人能聽懂的語言,因為他的語言是由以下兩種形式的規(guī)則由人的語言逐步抽象上去的: ----------------------------------------------------------- (1) a---> (B1)(B2)....(Bm) (2)[(op1)(p2)...(pn)]---->[o(pn)][o(p(n-1))].....[o(p1)o] ----------------------------------------------------------- 在這兩種形式中,從左到右均表示解釋.試寫一個魔王語言的解釋系統(tǒng),把 他的話解釋成人能聽得懂的話. 2. 基本要求: 用下述兩條具體規(guī)則和上述規(guī)則形式(2)實現(xiàn).設(shè)大寫字母表示魔王語言的詞匯 小寫字母表示人的語言的詞匯 希臘字母表示可以用大寫字母或小寫字母代換的變量.魔王語言可含人的詞匯. (1) B --> tAdA (2) A --> sae 3. 測試數(shù)據(jù): B(ehnxgz)B 解釋成 tsaedsaeezegexenehetsaedsae若將小寫字母與漢字建立下表所示的對應(yīng)關(guān)系,則魔王說的話是:"天上一只鵝地上一只鵝鵝追鵝趕鵝下鵝蛋鵝恨鵝天上一只鵝地上一只鵝". | t | d | s | a | e | z | g | x | n | h | | 天 | 地 | 上 | 一只| 鵝 | 追 | 趕 | 下 | 蛋 | 恨 |

    標簽: 語言 抽象

    上傳時間: 2014-12-02

    上傳用戶:jkhjkh1982

  • ApMl provides users with the ability to crawl the web and download pages to their computer in a dire

    ApMl provides users with the ability to crawl the web and download pages to their computer in a directory structure suitable for a Machine Learning system to both train itself and classify new documents. Classification Algorithms include Naive Bayes, KNN

    標簽: the provides computer download

    上傳時間: 2015-11-29

    上傳用戶:ywqaxiwang

  • We have a group of N items (represented by integers from 1 to N), and we know that there is some tot

    We have a group of N items (represented by integers from 1 to N), and we know that there is some total order defined for these items. You may assume that no two elements will be equal (for all a, b: a<b or b<a). However, it is expensive to compare two items. Your task is to make a number of comparisons, and then output the sorted order. The cost of determining if a < b is given by the bth integer of element a of costs (space delimited), which is the same as the ath integer of element b. Naturally, you will be judged on the total cost of the comparisons you make before outputting the sorted order. If your order is incorrect, you will receive a 0. Otherwise, your score will be opt/cost, where opt is the best cost anyone has achieved and cost is the total cost of the comparisons you make (so your score for a test case will be between 0 and 1). Your score for the problem will simply be the sum of your scores for the individual test cases.

    標簽: represented integers group items

    上傳時間: 2016-01-17

    上傳用戶:jeffery

  • The XML Toolbox converts MATLAB data types (such as double, char, struct, complex, sparse, logical)

    The XML Toolbox converts MATLAB data types (such as double, char, struct, complex, sparse, logical) of any level of nesting to XML format and vice versa. For example, >> project.name = MyProject >> project.id = 1234 >> project.param.a = 3.1415 >> project.param.b = 42 becomes with str=xml_format(project, off ) "<project> <name>MyProject</name> <id>1234</id> <param> <a>3.1415</a> <b>42</b> </param> </project>" On the other hand, if an XML string XStr is given, this can be converted easily to a MATLAB data type or structure V with the command V=xml_parse(XStr).

    標簽: converts Toolbox complex logical

    上傳時間: 2016-02-12

    上傳用戶:a673761058

  • 一個用神經(jīng)網(wǎng)絡(luò)方法實現(xiàn)人臉識別的程序

    一個用神經(jīng)網(wǎng)絡(luò)方法實現(xiàn)人臉識別的程序,來源于CMU的machine learning 課程作業(yè),具有參考價值

    標簽: 神經(jīng)網(wǎng)絡(luò) 人臉識別 程序

    上傳時間: 2013-11-28

    上傳用戶:515414293

  • Many of the pattern fi nding algorithms such as decision tree, classifi cation rules and c

    Many of the pattern fi nding algorithms such as decision tree, classifi cation rules and clustering techniques that are frequently used in data mining have been developed in machine learning research community. Frequent pattern and association rule mining is one of the few excep- tions to this tradition. The introduction of this technique boosted data mining research and its impact is tremendous. The algorithm is quite simple and easy to implement. Experimenting with Apriori-like algorithm is the fi rst thing that data miners try to do.

    標簽: 64257 algorithms decision pattern

    上傳時間: 2014-01-12

    上傳用戶:wangdean1101

  • Semantic analysis of multimedia content is an on going research area that has gained a lot of atten

    Semantic analysis of multimedia content is an on going research area that has gained a lot of attention over the last few years. Additionally, machine learning techniques are widely used for multimedia analysis with great success. This work presents a combined approach to semantic adaptation of neural network classifiers in multimedia framework. It is based on a fuzzy reasoning engine which is able to evaluate the outputs and the confidence levels of the neural network classifier, using a knowledge base. Improved image segmentation results are obtained, which are used for adaptation of the network classifier, further increasing its ability to provide accurate classification of the specific content.

    標簽: multimedia Semantic analysis research

    上傳時間: 2016-11-24

    上傳用戶:蟲蟲蟲蟲蟲蟲

  • 漢諾塔?。?! Simulate the movement of the Towers of Hanoi puzzle Bonus is possible for using animation

    漢諾塔!??! Simulate the movement of the Towers of Hanoi puzzle Bonus is possible for using animation eg. if n = 2 A→B A→C B→C if n = 3 A→C A→B C→B A→C B→A B→C A→C

    標簽: the animation Simulate movement

    上傳時間: 2017-02-11

    上傳用戶:waizhang

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