Weka - Your Comprehensive Data Mining Assistant

Dec 25, 2024

50 likes | 121 Views

Discover the power of Weka, a free data mining software that offers tools like visualisation, data editing, and management features for various applications. Explore Explorer, Experimenter, and more to efficiently handle data analysis tasks.

Share Presentation

Embed Code

halesm

Download Presentation

Weka - Your Comprehensive Data Mining Assistant

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

WEKA: free data mining software
Weka in few words Visualisation (curves, …) Tools (edit database) Main applications (Explorer, Experimenter, Knowledge Flow, Command Line) Program management (Quit,…)
Weka in few words: Explorer Visualisation Attribute selections Association rules Clusters Classifications
Weka in few words: Experimenter Validation Input datasets Methods
Weka in few words: Workflow

An Investigation into the Free/Open Source Software Phenomenon using Data Mining, Social Network Theory, and Agent-Based

An Investigation into the Free/Open Source Software Phenomenon using Data Mining, Social Network Theory, and Agent-Based Greg Madey Computer Science & Engineering University of Notre Dame UIUC - NSF Workshop on Continuous (Re)Design of Open Source Software

707 views • 43 slides

Weka: A Useful Tool for Air Quality Forecasting

Weka: A Useful Tool for Air Quality Forecasting . William F. Ryan Department of Meteorology The Pennsylvania State University wfr1@psu.edu. 2007 National Air Quality Conference, Orlando. Weka. The weka, or woodhen, is a bird native to New Zealand. Weka is

759 views • 27 slides

Data Mining

Data Mining. CS 157B Section 2 Keng Teng Lao. Overview. Definition of Data Mining Application of Data Mining. Data Mining . Refers to the mining or discovery of new information in terms of patterns or rules from vast amounts of data.

476 views • 15 slides

Data Mining

Data Mining. Dr. Tahar Kechadi Dr. Joe Carthy. Introduction. Motivation: Why data mining? What is data mining? Data Mining: On what kind of data? Data mining functionality Are all the patterns interesting? Classification of data mining systems Major issues in data mining.

1.46k views • 15 slides

Data Mining

Data Mining. IS698 Min Song. Introduction. Motivation: Why data mining? What is data mining? Data Mining: On what kind of data? Data mining functionality Are all the patterns interesting? Classification of data mining systems Data Mining Task Primitives

1.57k views • 45 slides

Weka 入門（セットアップ編）

Weka 入門（セットアップ編）. 静岡大学大学院理工学研究科阿部　秀尚 (hidenao@ks.cs.inf.shizuoka.ac.jp). Weka のセットアップ法. Windows/MacOS X 自己解凍形式（方法１）ファイルをダウンロードして実行使えるバージョンは 3.4.2 Java の SDK をインストール後に Weka をセットアップ（方法２）今後， Java を使う予定のある人にはお勧め. 方法１： Weka のダウンロード. http://panda.cs.Inf.shizuoka.ac.jp/~hidenao/work/weka/.

900 views • 10 slides

Data Mining: An Introduction

Data Mining: An Introduction. Wing Kee Ho Xiaohua Luan. Outline of Today Presentation. Definition of data mining Comparison of Data mining vs. DBMS Sample data mining tasks in daily life Data mining development. Definition of Data Mining.

373 views • 14 slides

Introduction to Weka

Introduction to Weka. Xingquan (Hill) Zhu Slides copied from Jeffrey Junfeng Pan (UST). Outline. Weka Data Source Feature selection Model building Classifier / Cross Validation Result visualization. WEKA. http://www.cs.waikato.ac.nz/ml/weka/ Data mining software in Java

2.03k views • 63 slides

Data Mining

Data Mining. What Is Data Mining?. Data Mining is the discovery of hidden knowledge, unexpected patterns and new rules in large databases Automating the process of searching patterns in the data. Objective of Data Mining. Any of four types of relationships are sought:

1.14k views • 77 slides

Data Mining

Data Mining. Knowledge Creation in Data Warehouses. Objectives. Understand what data mining is and identify where it might be used in a warehouse environment. Explain the techniques used by data mining Identify data mining tools Identify the possible results of a data mining query.

474 views • 25 slides

CHAPTER 17: DATA MINING BASICS

CHAPTER 17: DATA MINING BASICS. CHAPTER OBJECTIVE: What is Data Mining – Data Mining Definitions Data Mining Architecture Data Mining Applications Advantages and Disadvantages of Data Mining Data Mining Processes Data Mining Techniques. Knowledge Discovery.

733 views • 28 slides

Data Mining with Weka Putting it all together

Data Mining with Weka Putting it all together. Team members: Hao Zhou, Yujia Tian , Pengfei ‎ Geng , Yanqing Zhou, Ya Liu‎, Kexin Liu Director: Prof. Elke A. Rundensteiner Prof. Ian H. Witten. Outline. 5.1 The data mining process By Hao 5.2 Pitfalls and pratfalls

547 views • 43 slides

CHAPTER 17: DATA MINING BASICS

843 views • 28 slides

Data Mining Introduction

Data Mining Introduction. TYNE SYSTEM Chun-hung, Chou 2003.12.09. Outline. 1. Data Mining Overview 2. Functionalities 3. Software 4. R function 5. Example 6. Q & A. Data Mining Overview. Knowledge Discovery Process. 1. Data cleaning - remove noise and inconsistent data

482 views • 28 slides

Data Mining with DB

Data Mining with DB. 14. Introduction to Data Mining. Motivation: Why data mining? What is data mining? Data Mining: On what kind of data? Data mining functionality Are all the patterns interesting? Classification of data mining systems Major issues in data mining.

1.93k views • 102 slides

Spatial and Temporal Data Mining

Spatial and Temporal Data Mining. V. Megalooikonomou Introduction to Data Mining ( based on notes by Jiawei Han and Micheline Kamber and on notes by Christos Faloutsos). Agenda. Motivation: Why data mining? What is data mining? Data Mining: On what kind of data? Data mining functionality

1.17k views • 31 slides

Data Mining: Extracting Knowledge from Past Data

Data Mining: Extracting Knowledge from Past Data. Ming-Syan Chen Network Database Laboratory Electrical Engineering Department National Taiwan University. Outline. An introduction to data mining Challenging issues on data mining. Data Mining. Data mining: Knowledge discovery in databases

532 views • 26 slides

Data Mining

Data Mining. CMPT 455/826 - Week 10, Day 2. A Methodology for Evaluating and Selecting Data Mining Software. (based on Collier). Evaluation Categories. Performance is the ability to handle a variety of data sources in an efficient manner Functionality

356 views • 24 slides

More Related