Short description: GUI Ant-Miner is a tool for extracting classification rules from data. It is an updated version of a data mInIng algorithm called Ant-Miner (Ant Colony-based Data Miner), which was proposed in 2002 by Parpinelli, Lopes and Freitas. GUI Ant-Miner differs from the original algorithm as follows: It has a friendly graphical user interface, makes possible the use of ant populations within the Ant Colony Optimization (ACO) concept, data input file is standardized with the well-known Weka system, and runs on virtually any operating system since it is written in Java.
標(biāo)簽： classification description extracting Ant-Miner
上傳時間： 2013-12-18
上傳用戶：gonuiln
Pattern Analysis is the process of fi nding general relations in a set of data, and forms the core of many disciplines, from neural networks to so-called syn- tactical pattern recognition, from statistical pattern recognition to machine learning and data mInIng. Applications of pattern analysis range from bioin- formatics to document retrieval.
標(biāo)簽： the relations Analysis Pattern
上傳時間： 2017-09-07
上傳用戶：SimonQQ
ROST Content mInIng軟件,知識處理與內(nèi)容挖掘軟件,主要用于語義網(wǎng)絡(luò)挖掘,研究性軟件,功能很強大
上傳時間： 2015-04-07
上傳用戶：baibin8899
Smart Grids provide many benefits for society. Reliability, observability across the energy distribution system and the exchange of information between devices are just some of the features that make Smart Grids so attractive. One of the main products of a Smart Grid is to data. The amount of data available nowadays increases fast and carries several kinds of information. Smart metres allow engineers to perform multiple measurements and analyse such data. For example, information about consumption, power quality and digital protection, among others, can be extracted. However, the main challenge in extracting information from data arises from the data quality. In fact, many sectors of the society can benefit from such data. Hence, this information needs to be properly stored and readily available. In this chapter, we will address the main concepts involving Technology Information, Data mInIng, Big Data and clustering for deploying information on Smart Grids.
標(biāo)簽： Processing Cities Smart Data in
上傳時間： 2020-05-23
上傳用戶：shancjb
Smart Grids provide many benefits for society. Reliability, observability across the energy distribution system and the exchange of information between devices are just some of the features that make Smart Grids so attractive. One of the main products of a Smart Grid is to data. The amount of data available nowadays increases fast and carries several kinds of information. Smart metres allow engineers to perform multiple measurements and analyse such data. For example, information about consumption, power quality and digital protection, among others, can be extracted. However, the main challenge in extracting information from data arises from the data quality. In fact, many sectors of the society can benefit from such data. Hence, this information needs to be properly stored and readily available. In this chapter, we will address the main concepts involving Technology Information, Data mInIng, Big Data and clustering for deploying information on Smart Grids.
標(biāo)簽： Processing Cities Smart Data
上傳時間： 2020-05-25
上傳用戶：shancjb
W ?????????abooklikethistogether,manypeoplewhoneverhope to see their namesinprint get involved and provide alot of help. I wouldliketogivecreditwherecreditisdueandacknowledgethose people here. Firstandforemost,atleasthalfofthecreditforthisbookneedstogotomy wife,BrigitteKilger-Mattison. Brigittewasresponsible for editingall the mate- rial, creating all the graphics, and coordinating all the efforts of everyone else involvedinthisproject.Thisbookcouldnothavebeencompletedwithouther painstaking attention to detail, her dedication, and her loyalty.
標(biāo)簽： Data Warehousing mInIng and
上傳時間： 2020-05-27
上傳用戶：shancjb
ROST Content mInIng軟件簡稱ROST CM軟件，即內(nèi)容挖掘分析軟件。它是由武漢大學(xué)沈陽教授及其團隊研發(fā)的,專門用來進行文本內(nèi)容處理的一-款軟件。ROSTCM軟件具有分詞處理、高頻詞提取、情感分析、語義網(wǎng)絡(luò)分析、流量分析、可視化分析等一系列功能，一經(jīng)推出便受到社會和學(xué)界的廣泛關(guān)注。截至目前已有眾多學(xué)者、科研人員和學(xué)生等群體紛紛使用這一分析工具展開了相應(yīng)研究。
標(biāo)簽： ROSTCM
上傳時間： 2021-12-26
上傳用戶：
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