short introduction on Association Rule with definition & Example, are explained.
Association rules are if/then statements used to find relationship between unrelated data in information repository or relational database.
Parts of Association rule is explained with 2 measurements support and confidence.
types of association rule such as single dimensional Association Rule,Multi dimensional Association rules and Hybrid Association rules are explained with Examples.
Names of Association rule algorithm and fields where association rule is used is also mentioned.
Views: 85984
IT Miner - Tutorials,GK & Facts
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Views: 73204
Last Minute Tutorials
In this video FP growth algorithm is explained in easy way in data mining
Thank you for watching share with your friends
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Views: 126653
Well Academy
Lecture Series on Database Management System by Dr. S. Srinath,IIIT Bangalore. For more details on NPTEL visit http://nptel.iitm.ac.in
Views: 134228
nptelhrd
Watch Sample Class Recording: http://www.edureka.co/mahout?utm_source=youtube&utm_medium=referral&utm_campaign=apriori-algo
Apriori is an algorithm for frequent item set mining and association rule learning over transactional databases. It proceeds by identifying the frequent individual items in the database and extending them to larger and larger item sets as long as those item sets appear sufficiently often in the database.
The frequent item sets determined by Apriori can be used to determine association rules which highlight general trends in the database: this has applications in domains such as market basket analysis.
This video gives you a brief insight of Apriori algorithm.
Related Blogs:
http://www.edureka.co/blog/introduction-to-clustering-in-mahout/?utm_source=youtube&utm_medium=referral&utm_campaign=apriori-algo
http://www.edureka.co/blog/k-means-clustering/?utm_source=youtube&utm_medium=referral&utm_campaign=apriori-algo
Edureka is a New Age e-learning platform that provides Instructor-Led Live, Online classes for learners who would prefer a hassle free and self paced learning
environment, accessible from any part of the world.
The topics related to ‘Apriori Algorithm’ have extensively been covered in our course ‘Machine Learning with Mahout’.
For more information, please write back to us at [email protected]
Call us at US: 1800 275 9730 (toll free) or India: +91-8880862004
Views: 14512
edureka!
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Clickmyproject
This video is using Titanic data file that's embedded in R (see here: https://stat.ethz.ch/R-manual/R-devel/library/datasets/html/Titanic.html).
You can find both the data and the code here: https://github.com/A01203249/YouTube-Videos.git.
Use git clone to clone this repo locally and use the code.
Views: 48125
Ani Aghababyan
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myproject bazaar
Please feel free to get in touch with me :)
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Views: 57212
Last Minute Tutorials
Data Mining Using R (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information.
Data Mining Certification Training Course Content : https://www.excelr.com/data-mining/
Introduction to Data Mining Tutorials : https://youtu.be/uNrg8ep_sEI
What is Data Mining?
Big data!!! Are you demotivated when your peers are discussing about data science and recent advances in big data. Did you ever think how Flip kart and Amazon are suggesting products for their customers? Do you know how financial institutions/retailers are using big data to transform themselves in to next generation enterprises? Do you want to be part of the world class next generation organisations to change the game rules of the strategy making and to zoom your career to newer heights?
Here is the power of data science in the form of Data mining concepts which are considered most powerful techniques in big data analytics.
Data Mining with R unveils underlying amazing patterns, wonderful insights which go unnoticed otherwise, from the large amounts of data. Data mining tools predict behaviours and future trends, allowing businesses to make proactive, unbiased and scientific-driven decisions. Data mining has powerful tools and techniques that answer business questions in a scientific manner, which traditional methods cannot answer. Adoption of data mining concepts in decision making changed the companies, the way they operate the business and improved revenues significantly.
Companies in a wide range of industries such as Information Technology, Retail, Telecommunication, Oil and Gas, Finance, Health care are already using data mining tools and techniques to take advantage of historical data and to create their future business strategies.
Data mining can be broadly categorized into two branches i.e. supervised learning and unsupervised learning. Unsupervised learning deals with identifying significant facts, relationships, hidden patterns, trends and anomalies. Clustering, Principle Component Analysis, Association Rules, etc., are considered unsupervised learning. Supervised learning deals with prediction and classification of the data with machine learning algorithms. Weka is most popular tool for supervised learning.
Topics You Will Learn…
Unsupervised learning:
Introduction to datamining
Dimension reduction techniques
Principal Component Analysis (PCA)
Singular Value Decomposition (SVD)
Association rules / Market Basket Analysis / Affinity Filtering
Recommender Systems / Recommendation Engine / Collaborative Filtering
Network Analytics – Degree centrality, Closeness Centrality, Betweenness Centrality, etc.
Cluster Analysis
Hierarchical clustering
K-means clustering
Supervised learning:
Overview of machine learning / supervised learning
Data exploration methods
Basic classification algorithms
Decision trees classifier
Random Forest
K-Nearest Neighbours
Bayesian classifiers: Naïve Bayes and other discriminant classifiers
Perceptron and Logistic regression
Neural networks
Advanced classification algorithms
Bayesian Networks
Support Vector machines
Model validation and interpretation
Multi class classification problem
Bagging (Random Forest) and Boosting (Gradient Boosted Decision Trees)
Regression analysis
Tools You Will Learn…
R:
R is a programming language to carry out complex statistical computations and data visualization. R is also open source software and backed by large community all over the world who are contributing to enhancing the capability. R has many advantages over other tools available in the market and it has been rated No.1 among the data scientist community.
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Data Mining with Weka: online course from the University of Waikato
Class 1 - Lesson 3: Exploring datasets
http://weka.waikato.ac.nz/
Slides (PDF):
http://goo.gl/IGzlrn
https://twitter.com/WekaMOOC
http://wekamooc.blogspot.co.nz/
Department of Computer Science
University of Waikato
New Zealand
http://cs.waikato.ac.nz/
Views: 78892
WekaMOOC
Data mining recently made big news with the Cambridge Analytica scandal, but it is not just for ads and politics. It can help doctors spot fatal infections and it can even predict massacres in the Congo.
Hosted by: Stefan Chin
Head to https://scishowfinds.com/ for hand selected artifacts of the universe!
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Sources:
https://www.aaai.org/ojs/index.php/aimagazine/article/viewArticle/1230
https://www.theregister.co.uk/2006/08/15/beer_diapers/
https://www.theatlantic.com/technology/archive/2012/04/everything-you-wanted-to-know-about-data-mining-but-were-afraid-to-ask/255388/
https://www.economist.com/node/15557465
https://blogs.scientificamerican.com/guest-blog/9-bizarre-and-surprising-insights-from-data-science/
https://qz.com/584287/data-scientists-keep-forgetting-the-one-rule-every-researcher-should-know-by-heart/
https://www.amazon.com/Predictive-Analytics-Power-Predict-Click/dp/1118356853 http://dml.cs.byu.edu/~cgc/docs/mldm_tools/Reading/DMSuccessStories.html
http://content.time.com/time/magazine/article/0,9171,2058205,00.html
https://www.nytimes.com/2012/02/19/magazine/shopping-habits.html?pagewanted=all&_r=0
https://www2.deloitte.com/content/dam/Deloitte/de/Documents/deloitte-analytics/Deloitte_Predictive-Maintenance_PositionPaper.pdf
https://www.cs.helsinki.fi/u/htoivone/pubs/advances.pdf
http://cecs.louisville.edu/datamining/PDF/0471228524.pdf
https://bits.blogs.nytimes.com/2012/03/28/bizarre-insights-from-big-data
https://scholar.harvard.edu/files/todd_rogers/files/political_campaigns_and_big_data_0.pdf
https://insights.spotify.com/us/2015/09/30/50-strangest-genre-names/
https://www.theguardian.com/news/2005/jan/12/food.foodanddrink1
https://adexchanger.com/data-exchanges/real-world-data-science-how-ebay-and-placed-put-theory-into-practice/
https://www.theverge.com/2015/9/30/9416579/spotify-discover-weekly-online-music-curation-interview
http://blog.galvanize.com/spotify-discover-weekly-data-science/
Audio Source:
https://freesound.org/people/makosan/sounds/135191/
Image Source: https://commons.wikimedia.org/wiki/File:Swiss_average.png
Views: 144222
SciShow
Final presentation for Data Mining Seminar
Views: 152
Boshen Lyu
23-minute beginner-friendly introduction to data mining with WEKA. Examples of algorithms to get you started with WEKA: logistic regression, decision tree, neural network and support vector machine. Update 7/20/2018: I put data files in .ARFF here http://pastebin.com/Ea55rc3j and in .CSV here http://pastebin.com/4sG90tTu Sorry uploading the data file took so long...it was on an old laptop.
Views: 448764
Brandon Weinberg
More Data Mining with Weka: online course from the University of Waikato
Class 1 - Lesson 1: Introduction
http://weka.waikato.ac.nz/
Slides (PDF):
http://goo.gl/Le602g
https://twitter.com/WekaMOOC
http://wekamooc.blogspot.co.nz/
Department of Computer Science
University of Waikato
New Zealand
http://cs.waikato.ac.nz/
Views: 15812
WekaMOOC
Buy Software engineering books(affiliate):
Software Engineering: A Practitioner's Approach by McGraw Hill Education
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Software Engineering: A Practitioner's Approach by McGraw Hill Education
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Software Engineering by Pearson Education
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Software Engineering: Principles and Practices by Oxford
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-------------------------------
find relevant notes at-https://viden.io/
Views: 108781
LearnEveryone
Google Tech Talks
August 7, 2007
ABSTRACT
This is the Google campus version of Stats 202 which is being taught at Stanford this summer. I will follow the material from the Stanford class very closely. That material can be found at www.stats202.com. The main topics are exploring and visualizing data, association analysis, classification, and clustering. The textbook is Introduction to Data Mining by Tan, Steinbach and Kumar. Googlers are welcome to attend any classes which they think might be of interest to them.
Google engEDU
Speaker: David Mease
Views: 353
GoogleTalksArchive
Frequent Pattern Growth algorithm is a tree based algorithm used for Association Rule Mining. It transforms the transactional database to a tree, which is used for mining frequent patterns. The frequent patterns grow as we traverse the tree deeper.
It is better than apriori algorithm because database is read only once for creating FP Tree and then the tree is subsequently used to recursively create conditional FP trees to mine it.
Note to viewer: if you already know FP tree creation, you can start watching this video from 20 minutes.
Views: 43871
Moh'd Shakeb Baig
Advanced Data Mining with Weka: online course from the University of Waikato
Class 4 - Lesson 1: What is distributed Weka?
http://weka.waikato.ac.nz/
Slides (PDF):
https://goo.gl/msswhT
https://twitter.com/WekaMOOC
http://wekamooc.blogspot.co.nz/
Department of Computer Science
University of Waikato
New Zealand
http://cs.waikato.ac.nz/
Views: 1832
WekaMOOC
Advanced Data Mining with Weka: online course from the University of Waikato
Class 2 - Lesson 1: Incremental classifiers in Weka
http://weka.waikato.ac.nz/
Slides (PDF):
https://goo.gl/4vZhuc
https://twitter.com/WekaMOOC
http://wekamooc.blogspot.co.nz/
Department of Computer Science
University of Waikato
New Zealand
http://cs.waikato.ac.nz/
Views: 3182
WekaMOOC
Data Mining with Weka: online course from the University of Waikato
Class 4 - Lesson 4: Logistic regression
http://weka.waikato.ac.nz/
Slides (PDF):
http://goo.gl/augc8F
https://twitter.com/WekaMOOC
http://wekamooc.blogspot.co.nz/
Department of Computer Science
University of Waikato
New Zealand
http://cs.waikato.ac.nz/
Views: 32090
WekaMOOC
Some extra features of the Data Mining Tool. Heatmaps and Gene Set Enrichment.
Views: 59
QMRIBioinf
Learn how to make classes, attributes, and methods in this UML Class Diagram tutorial. There's also in-depth training and examples on inheritance, aggregation, and composition relationships.
UML (or Unified Modeling Language) is a software engineering language that was developed to create a standard way of visualizing the design of a system. And UML Class Diagrams describe the structure of a system by showing the system’s classes and how they relate to one another.
This tutorial explains several characteristics of class diagrams. Within a class, there are attributes, methods, visibility, and data types. All of these components help identify a class and explain what it does.
There are also several different types of relationships that exist within UML Class Diagrams. Inheritance is when a child class (or subclass) takes on all the attributes and methods of the parent class (or superclass). Association is a very basic relationship where there's no dependency. Aggregation is a relationship where the part can exist outside the whole. And finally, Composition is when a part cannot exist outside the whole. A class would be destroyed if the class it's related to is destroyed.
Further UML Class Diagram information: https://www.lucidchart.com/pages/uml-class-diagram
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Views: 747738
Lucidchart
More Data Mining with Weka: online course from the University of Waikato
Class 1 - Lesson 5: The Command Line interface
http://weka.waikato.ac.nz/
Slides (PDF):
http://goo.gl/Le602g
https://twitter.com/WekaMOOC
http://wekamooc.blogspot.co.nz/
Department of Computer Science
University of Waikato
New Zealand
http://cs.waikato.ac.nz/
Views: 9849
WekaMOOC
In our weekly #DataTalk, we had a chance to talk with Meta Brown about her work in data science and her latest book: Data Mining for Dummies. You can learn more about her by going to her website:
http://www.metabrown.com/
You can read a full transcription of this video by going to:
http://ex.pn/metabrown
You can learn about upcoming #DataTalk events and tweetchats:
http://experian.com/datatalk
Views: 1531
Experian
Terracon accomplishes data mining with a GIS-based platform that manages vast amounts of geospatial information from thousands of locations across the country. This provides our clients with better information right at the start of a project.
Views: 1547
Terraconconsultants
Views: 66
Abdul Malik
Lecture notes: http://learning.stat.purdue.edu/mlss/_media/mlss/han.pdf
Mining Heterogeneous Information Networks
Multiple typed objects in the real world are interconnected, forming complex heterogeneous information networks. Different from some studies on social network analysis where friendship networks or web page networks form homogeneous information networks, heterogeneous information network reflect complex and structured relationships among multiple typed objects. For example, in a university network, objects of multiple types, such as students, professors, courses, departments, and multiple typed relationships, such as teach and advise are intertwined together, providing rich information.
We explore methodologies on mining such structured information networks and introduce several interesting new mining methodologies, including integrated ranking and clustering, classification, role discovery, data integration, data validation, and similarity search. We show that structured information networks are informative, and link analysis on such networks becomes powerful at uncovering critical knowledge hidden in large networks. The tutorial also presents a few promising research directions on mining heterogeneous information networks.
See other lectures at Purdue MLSS Playlist: http://www.youtube.com/playlist?list=PL2A65507F7D725EFB&feature=view_all
Views: 1101
Purdue University
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Views: 19
Clickmyproject
नमस्कार दोस्तों,आज की वीडियो में में आप सभी को DATA MINING के बारे में बताने जा रहा हूँ की आखिर DATA MINING क्या होती है और क्या ये हमारे किसी काम आती हैं या नहीं और आखिर हमारे ज़िन्दगी में इसकी कितनी जरुरत है। आशा करता हूँ आपको ये वीडियो पसंद आएगी अगर आपको वीडियो पसंद आये तो वीडियो को LIKE SHARE और चैनल को SUBSCRIBE जरूर से करे।
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subscribe our channel on youtube: https://www.youtube.com/channel/UCR_kAPwG59SxWRaUfzk3qoQ
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Views: 11380
Dropout Technical
More Data Mining with Weka: online course from the University of Waikato
Class 1 - Lesson 6: Working with big data
http://weka.waikato.ac.nz/
Slides (PDF):
http://goo.gl/Le602g
https://twitter.com/WekaMOOC
http://wekamooc.blogspot.co.nz/
Department of Computer Science
University of Waikato
New Zealand
http://cs.waikato.ac.nz/
Views: 10098
WekaMOOC
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Machine Learning Group at the University of Waikato
Project Software Book Publications People Related
Weka 3: Data Mining Software in Java
Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
Found only on the islands of New Zealand, the Weka is a flightless bird with an inquisitive nature. The name is pronounced like this, and the bird sounds like this.
Weka is open source software issued under the GNU General Public License.
We have put together several free online courses that teach machine learning and data mining using Weka. Check out the website for the courses for details on when and how to enrol. The videos for the courses are available on Youtube.
Yes, it is possible to apply Weka to big data!
Views: 331
Kodkolik.Net | Yazılımın Yeni Adresi
Advanced Data Mining with Weka: online course from the University of Waikato
Class 4 - Lesson 6: Application: Image classification
http://weka.waikato.ac.nz/
Slides (PDF):
https://goo.gl/msswhT
https://twitter.com/WekaMOOC
http://wekamooc.blogspot.co.nz/
Department of Computer Science
University of Waikato
New Zealand
http://cs.waikato.ac.nz/
Views: 7694
WekaMOOC
Junling Hu presents a high level overview of data mining at the "Data Mining Case Study" meetup at the HackerDojo in Mountain View, Ca on Aug 17th 2013.
Views: 1524
Stoney Vintson
Neural network in ai (Artificial intelligence)
Neural network is highly interconnected network of a large number of processing elements called neuron architecture motivated from brain.
Neuron are interconnected to synapses which provide input from other neurons which intern provides output i.e input to other neurons.
Neuron are in massive therefore they provide distributed network.
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Views: 9183
CaelusBot
This tutorial will show you how to analyze text data in R. Visit https://deltadna.com/blog/text-mining-in-r-for-term-frequency/ for free downloadable sample data to use with this tutorial. Please note that the data source has now changed from 'demo-co.deltacrunch' to 'demo-account.demo-game'
Text analysis is the hot new trend in analytics, and with good reason! Text is a huge, mainly untapped source of data, and with Wikipedia alone estimated to contain 2.6 billion English words, there's plenty to analyze. Performing a text analysis will allow you to find out what people are saying about your game in their own words, but in a quantifiable manner. In this tutorial, you will learn how to analyze text data in R, and it give you the tools to do a bespoke analysis on your own.
Views: 65998
deltaDNA
Data Mining with Weka: online course from the University of Waikato
Class 2 - Lesson 2: Training and testing
http://weka.waikato.ac.nz/
Slides (PDF):
http://goo.gl/D3ZVf8
https://twitter.com/WekaMOOC
http://wekamooc.blogspot.co.nz/
Department of Computer Science
University of Waikato
New Zealand
http://cs.waikato.ac.nz/
Views: 72678
WekaMOOC
What is Linear Regression? In this video I explain what linear regression is, why it’s used and briefly show you how to implement it in Python using scikit learn and statmodels. I also explain R squared, t-value and p-value.
More information and learning resources on Linear Regression
If this has been useful, then consider giving your support by buying me a coffee https://ko-fi.com/pythonprogrammer
Introduction to Statistical Learning - http://bit.ly/2ELFL6Z (Free PDF of Book)
#linearregression #linearregressionpython #machinelearningalgorithms
Views: 1324
Python Programmer
This video runs through an example script on how to estimate panel data models in R using plm(). By appeal to lm() and lmer(), I show that plm() estimates what we think it should estimate. I also show how to cluster standard errors in R. Here are some resources to which I refer in the video:
I posted these scripts on my econometrics website. metrics.tonycookson.com. They are called clusterFunctions.R and exampleofclusteringinR.R, and they are available for download there.
Mahmoud Arai's Clustering Functions. http://people.su.se/~ma/clustering.pdf
Mitchell Peterson's Test Data (kept referring to him as Thompson in the video, sorry!). http://www.kellogg.northwestern.edu/faculty/petersen/htm/papers/se/test_data.htm
And some background reading on this.
Peterson 2009 can be found here in earlier WP version. http://ideas.repec.org/p/nbr/nberwo/11280.html
Thompson 2011 can be found here. http://schwert.ssb.rochester.edu/f532/JFE11_ST.pdf
To address the question about ML/REML. Here is a useful set of slides on how to specify the likelihood. http://www.stat.wisc.edu/~ane/st572/notes/lec21.pdf As I remember it, REML focuses on estimating the error components independently of the systematic part of the regression model. On an intuitive level, this amounts to building in a degrees of freedom correction. There is much more out there on a Google search of "REML vs. ML in random effects"
Views: 9279
intromediateecon
Download this sum PDF from link below
http://britsol.blogspot.in/2017/10/decision-tree-algorithm-pdf.html?m=1
book name: techmax publications datawarehousing and mining by arti deshpande n pallavi halarnkar
Views: 57501
fun 2 code
In this video we are using PHP to fetch data from our database we made earlier in previous videos.
Please like share and subscribe
Views: 1405
Rameez Safdar
*For the playlist , please click the below Link:
https://www.youtube.com/watch?v=L7tEs7kraTQ&list=PL-1QQC56x1gGsEWQP1dZ4rOQvKyUhdttW
#Data_science_alive #Machine_learning #No_1_Trending_video #Machine_learning_Python_R
*Visit Our website : https://datasciencealive.wordpress.com/machine-learning/
*Please click the following link to download the dataset: https://datasciencealive.wordpress.com/data-set/
*In this session we will look into topics that will be covered on the data preprocessing techniques using pandas in python . In machine learning most of the time will be spend on data preprocessing , data mining and feature extraction . Hence please listen to this topic more carefully .
*This is a Data science course . This is a full fledge course for free and we will cove all the main topics on the machine learning algorithm. This course is specifically designed to address all the queries from beginners to expert . Artificial intelligence ( AI ) is a bigger umbrella ,In that Machine learning ( ML ) and Deep Learning ( DL ) are part of Artificial Intelligence.
*In this video we will have an overview on the topics that will be covered. On high level it will be
*Data Preprocessing
*Supervised Learning - Algorithm
*Classification
*Regression
*Association
*Unsupervised learning - Algorithm
*Clustering
*Dimensionality Reduction (PCA)
*Semi -Supervised learning
*Re- Enforcement learning
*Best approach for Model selection
*Intro to Deep Learning
The above topics will be covered in-detail on the upcoming session which you can find it in the playlist .
*For the playlist , please click the below Link:
https://www.youtube.com/watch?v=L7tEs7kraTQ&list=PL-1QQC56x1gGsEWQP1dZ4rOQvKyUhdttW
#Data_science_alive #Machine_learning #Machine_learning_Python_R #No_1_Trending_video
Views: 86
Data Science Alive
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Creating a file association in Microsoft Excel will have those types of files automatically open in the Excel program. Create a file association in Microsoft Excel with help from an experienced computer services technician in this free video clip.
Expert: William Fisher
Bio: William Fisher is an IT professional serving in such roles as IT Instructor, IT Trainer, Project Manager, Network Engineer, Technology Consultant and Computer Services Technician.
Filmmaker: Jeff Goodey
Series Description: Microsoft Excel is still one of the most powerful spreadsheet creation tools on the planet, even years after its original release. Get tips for Microsoft Excel with help from an experienced computer services technician in this free video series.
Views: 1702
eHowTech
Weka,
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Weka, makine öğrenimi amacıyla Waikato Üniversitesinde geliştirilmiş ve "Waikato Environment for Knowledge Analysis" kelimelerinin baş harflerinden oluşmuş yazılımın ismidir. Günümüzde yaygın kullanımı olan çoğu makine öğrenimi algoritmalarını ve metotlarını içermektedir.
Java dilinde geliştirilmiş olması ve kütüphanelerinin .jar dosyaları halinde geliyor olması sayesinde, Java dilinde yazılan projelere kolayce entegre edilebilmesi kullanımını daha da yaygınlaştırmıştır
Yazılım, GNU Genel Kamu Lisansı ile dağıtılmaktadır.
Weka, tamamen modüler bir tasarıma sahip olup, içerdiği özelliklerle veri kümeleri üzerinde görselleştirme, veri analizi, iş zekası uygulamaları, veri madenciliği gibi işlemler yapabilmektedir. Weka yazılımı, kendisine özgü olarak bir .arff uzantısı desteği ile gelmektedir. Ancak Weka yazılımının içerisinde CSV dosyalarını da ARFF formatına çevirmeye yarayan araçlar mevcuttur. Temel olarak aşağıdaki 3 Veri Madenciliği işlemi Weka ile yapılabilir:
Sınıflandırma (Classification)
Bölütleme (Clustering)
İlişkilendirme (Association)
Ayrıca yukarıdaki işlemlere ilave olarak, veri kümeleri üzerinde ön ve son işlemler yapılabilir
Veri Ön işleme (Data Pre-Processing)
Görselleme (Visualization)
Son olarak Weka Kütüphanesi'nde veri kümelerini içeren dosyalar üzerinde çalışan çok sayıda hazır fonksiyon bulunmaktadır.
Machine Learning Group at the University of Waikato
Project Software Book Publications People Related
Weka 3: Data Mining Software in Java
Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
Found only on the islands of New Zealand, the Weka is a flightless bird with an inquisitive nature. The name is pronounced like this, and the bird sounds like this.
Weka is open source software issued under the GNU General Public License.
We have put together several free online courses that teach machine learning and data mining using Weka. Check out the website for the courses for details on when and how to enrol. The videos for the courses are available on Youtube.
Yes, it is possible to apply Weka to big data!
Views: 799
Kodkolik.Net | Yazılımın Yeni Adresi
* Data Scraping || Data Extraction || Data Crawling || Data Mining from any source of Website.
* Data Scraping & Extraction - Copy Paste data from any Website
* Data Mining & Crawling from Yellowpages, Yelp, Yell, Whitepages, etc..
* PDF to MS-Excel / MS-Word data Conversion.
* Online Research || Market Research || Specific Niche Research || Product Research.
* Researching Contact Details of specific industry / persons / professional for particular Titles.
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Numb3r TekSolution