Tiedon louhinta Data Mining

Sep 12, 2012

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Tiedon louhinta Data Mining

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1. Tiedon louhinta�Data Mining� Jaana Diakite Mari Pursiainen Markus Laine Lauri Porras 27.4.2009

Data Mining: Data

What is Data?. Collection of data objects and their attributesAn attribute is a property or characteristic of an objectExamples: eye color of a person, temperature, etc.Attribute is also known as variable, field, characteristic, or featureA collection of attributes describe an objectObject is

1.03k views • 61 slides

Data Mining: Data

Data Mining: Data. Lecture Notes for Chapter 2 CSE 572 Data Mining Instructor: Jieping Ye Department of Computer Science and Engineering Arizona State University. What is Data?. Collection of data objects and their attributes An attribute is a property or characteristic of an object

988 views • 67 slides

Data Mining: Proses Data Mining

Data Mining: Proses Data Mining. Romi Satria Wahon o romi@romisatriawahono.net http://romisatriawahono.net +6281586220090. Romi Satria Wahono. SD Sompok Semarang (1987) SMPN 8 Semarang (1990) SMA Taruna Nusantara , Magelang (1993)

1.85k views • 115 slides

Data Mining: Proses Data Mining

Data Mining: Proses Data Mining. Romi Satria Wahon o romi@romisatriawahono.net http://romisatriawahono.net 0815-86220090. Romi Satria Wahono. SD Sompok Semarang (1987) SMPN 8 Semarang (1990) SMA Taruna Nusantara , Magelang (1993)

2.93k views • 115 slides

Data Mining: Data

Data Mining: Data. Lecture Notes for Chapter 2 Introduction to Data Mining by Tan, Steinbach, Kumar. What is Data?. Collection of data objects and their attributes An attribute is a property or characteristic of an object Examples: eye color of a person, temperature, etc.

1.09k views • 79 slides

Data Mining: P enelitian Data Mining

Data Mining: P enelitian Data Mining. Romi Satria Wahon o romi@romisatriawahono.net http://romisatriawahono.net +6281586220090. Romi Satria Wahono. SD Sompok Semarang (1987) SMPN 8 Semarang (1990) SMA Taruna Nusantara , Magelang (1993)

376 views • 19 slides

Data Mining

Data Mining. Lecture 6. Course Syllabus. Case Study 1 : Working and experiencing on the properties of The Retail Banking Data Mart (Week 4 –Assignment1) Data Analysis Techniques ( Week 5 ) Statistical Background Trends/ Outliers/Normalizations Principal Component Analysis

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Data Mining

Data Mining. Introduction. Finding interesting trends or pattern in large datasets. Statistics : exploratory data analysis Artificial intelligence : knowledge discovery and machine learning. Scalability with respect to data size.

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Data mining

Data mining. Temă de casă Rețete de Calculatoare si Internet. Ing. Olga Aldea Prof. Coordonator Ștefan Stăncescu. Introducere (1).

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Data Mining: Data

Data Mining: Data. Lecture Notes for Chapter 2 Introduction to PCA (Principal Component Analysis). What is PCA?. Stands for “Principal Component Analysis” Useful technique in many applications such as face recognition, image compression, finding patterns in data of high dimension

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Data Mining: Data

Data Mining: Data. Lecture 3 TIES445 Data mining Nov-Dec 2007 Sami Äyrämö. Data quality. GIGO – Garbage In, Garbage Out Effectiveness of DM exercise depends on the quality of data Data quality concerns individual measurements (records and fields) collections of observations

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Data Mining: Data

Data Mining: Data. Lecture Notes for Chapter 2 Introduction to Data Mining by Tan, Steinbach, Kumar (edited by S. Parthasarathy 3/2007). What is Data?. Collection of data objects and their attributes An attribute is a property or characteristic of an object

743 views • 42 slides

Data Mining: Data

Data Mining: Data. Introduction to Data Mining by Tan, Steinbach, Kumar. What is Data?. Collection of data objects and their attributes An attribute is a property or characteristic of an object Examples: eye color of a person, temperature, etc.

1.14k views • 68 slides

Tiedon esittäminen

Tiedon esittäminen. Analoginen ja numeerinen tieto. Analoginen kello: Osoittimet voi olla missä asennossa hyvänsä, niissä tieto on siten jatkuvaa.Kellon aika katsotaan osoittimien asennon perusteella.Ihmiset voivat olla hieman eri mieltä kellon ajoista. Numeerinen eli digitaalinen kello:

288 views • 10 slides

Data Mining: Data

Data Mining: Data. Lecture Notes for Chapter 2 Introduction to Data Mining by Minqi Zhou. Precap –What’s Data Mining?. Many Definitions Non-trivial extraction of implicit, previously unknown and potentially useful information from data

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Data Mining

Data Mining.

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Data Mining

Data Mining. Introduction. What is data mining. The discovery of new information in terms of patterns or rules from vast amounts of data Process of semi-automatically analyzing large databases to find patterns that are: valid: hold on new data with some certainity

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Data Mining: Data

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Data Mining: Data

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