Preprocessing Steps to Make Data More Suitable for Data Mining: Example: An ordinal attribute drink_size corresponds to the size of drinks available at.
What's in an example? Relations flat files
There are different types of attributes. – Nominal:Examples: ID numbers eye color
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 ...
3 janv. 2020 Abstract—Ordinal data are common in many data mining and ... and ordinal attributes is common
Also called samples examples
What's in an example? Relations flat files
Keywords: attribute evaluation ordinal attributes
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. Data Mining Lecture 2 Example: Attribute values for ID and age are integers ... Ordinal attribute: distinctness & order.
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
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 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
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
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
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