Categorical data is a type of data that can be divided or classified into groups. Understand the definition and examples of categorical data, learn to distinguish categorical data from quantitative data, and explore the uses of categorical data. ...
Now that we have a formula, we can plug that formula into a few examples! Both example problems will involve interpreting two categorical data sets by asking a specific question about the data. Examples of How to Compare Two or More Sets of Categorical DataExample...
The task of outlier detection is to find small groups of data objects that are exceptional when compared with rest large amount of data. Detection of such ... Jinchao,Ji,and,... - 《Knowledge Based Systems》 被引量: 155发表: 2012年 Clustering categorical data sets using tabu search techniq...
Several examples of categorized data from epidemiological studies are analyzed to illustrate that more informative analysis than tests of independence can ... JE Grizzle,GG Koch - 《Environmental Health Perspectives》 被引量: 6发表: 1979年 CATDAT : A Program for Parametric and Nonparametric Categoric...
data, small samples, multicategory data, and matched pairs; more than 100 examples of real data sets and more than 200 exercises Writing in an applied, nontechnical style, Alan Agresti illustrates methods using a wide variety of real data, including alcohol, cigarette, and marijuana use by ...
Introduces the key concepts in the analysis of categoricaldata with illustrative examples and accompanying R code This book is aimed at all those who wish to discover how to analyze categorical data without getting immersed in complicated mathematics and without needing to wade through a large amount...
2.2.4Data Types and Conversion The attributes in a data set can be of different types, such as continuous numeric (interest rate), integer numeric (credit score), or categorical. In some data sets, credit score is expressed as ordinal or categorical (poor, good, excellent). Different data ...
Thus, we propose a modified categorical SCM (MC-SCM) for grouping categorical data sets. The proposed MC-SCM algorithm is able to get good performance for clustering categorical data without any initial value that can also find an optimal number of clusters. Some examples are presented to ...
y_label_encoded = final_label_encoded['price']# Split the data into train and test sets for One-Hot EncodingX_train_one_hot, X_test_one_hot, y_train_one_hot, y_test_one_hot = train_test_split(X_one_hot, y_one_hot, test_size=0.2, random_state=42)# Split the data into train...
All methods are illustrated with analyses of real data examples, many from recent subject area journal articles. These analyses are highlighted in the text, and are more detailed than is typical, providing discussion of the context and background of the problem, model checking, and scientific ...