Data Objects and Attribute Types • Basic Statistical Descriptions of

Preprocessing Steps to Make Data More Suitable for Data Mining: Example: An ordinal attribute drink_size corresponds to the size of drinks available at.

Data Mining

What's in an example? Relations flat files

Data Mining: Data

There are different types of attributes. – Nominal:Examples: ID numbers eye color

Data Lecture Notes for Chapter 2 Introduction to Data Mining 2nd

27 janv. 2021 What is Data? Collection of data objects and their attributes. An attribute is a property or characteristic of an object. – Examples: eye ...

A Unified Entropy-Based Distance Metric for Ordinal-and-Nominal

3 janv. 2020 Abstract—Ordinal data are common in many data mining and ... and ordinal attributes is common

CSE5243 Intro. to Data Mining

Also called samples examples

Data Mining: Practical Machine Learning Tools and Techniques

What's in an example? Relations flat files

Evaluation of ordinal attributes at value level

Keywords: attribute evaluation ordinal attributes

Data Mining: Data

Introduction to Data Mining. 1/2/2009. 4. Different attributes can be mapped to the same set of values. ? Example: Attribute values for ID and age are 

Basic Data Mining Techniques

Basic Data Mining Techniques. Data Mining Lecture 2 Example: Attribute values for ID and age are integers ... Ordinal attribute: distinctness & order.

Data Mining and Analysis - Cambridge

CHAPTER 1Data Mining and Analysis Data mining is the process of discovering insightful interesting and novel patterns as well as descriptive understandable and predictive models from large-scale data We begin this chapter by looking at basic properties of data modeled as a data matrix

Basic Data Mining Techniques - Uppsala University

The type of an attribute depends on which of the following properties/operations it possesses: Distinctness: = Order: < > Differences are+ -meaningful : Ratios are * /meaningful Nominal attribute: distinctness Ordinal attribute: distinctness & order Interval attribute: distinctness order & meaningful differences

Data Mining Classification: Basic Concepts Decision Trees

Data Mining Classification: Basic Concepts Decision Trees and Model Evaluation Data Mining Classification: Basic Concepts Decision Trees and Model Evaluation Lecture Notes for Chapter 4 Introduction to Data Mining by Tan Steinbach Kumar © TanSteinbach Kumar Introduction to Data Mining 4/18/2004 1 © TanSteinbach Kumar

Data Mining Classification: Alternative Techniques

2/08/2021 Introduction to Data Mining 2 nd Edition 11 Estimate Probabilities from Data • For continuous attributes: – Discretization: Partition the range into bins: Replace continuous value with bin value – Attribute changed from continuous to ordinal – Probability density estimation: Assume attribute follows a normal distribution

Basic Data Mining Techniques

The type of an attribute depends on which of the following properties it possesses: Distinctness: = ? Order: < > Addition: + - Multiplication: * / Nominal attribute: distinctness Ordinal attribute: distinctness & order Interval attribute: distinctness order & addition Ratio attribute: all 4 properties 5 6

Searches related to ordinal attribute example in data mining filetype:pdf

Ordinal attributes are also called “numeric” or “continuous” Preparing the input • No quality data no quality mining results! • Quality decisions must be based on quality data • Data extraction integration transformation cleaning and reduction comprise the majority

What is a continuous attribute in data mining?

• Continuous Attribute – Has real numbers as attribute values – Examples: temperature, height, or weight – Practically, real values can only be measured and represented using a finite number of digits – Continuous attributes are typically represented as floating- point variables Data Mining Lecture 2 10

Can nominal values be ordinal?

If numbers are used as IDs or names of categories,the corresponding attribute is actually nominal. Note that it doesn't make sense to order the values of such attributes. Also note that some nominal values canbe ordinal: ? Distinction between nominal and ordinal not always clear (e.g. attribute “outlook” – is there an ordering?)

What are some examples of data mining?

• Examples: rankings (e.g., taste of potato chips on a scale from 1-10), grades, height in {tall, medium, short} – Interval • Examples: calendar dates, temperatures in Celsius or Fahrenheit. – Ratio • Examples: temperature in Kelvin, length, time, counts Data Mining Lecture 2 6

What is an example of an ordinal scale?

– Ordinal • Examples: rankings (e.g., taste of potato chips on a scale from 1-10), grades, height in {tall, medium, short} – Interval