Data Mining Classification: Basic Concepts and Techniques Lecture Notes for Chapter 3 Introduction to Data Mining, 2nd Edition by Tan, Steinbach, Karpatne, Kumar 2/1/2021 …

Classification consists of predicting a certain outcome based on a given input. In order to predict the outcome, the algorithm processes a training set containing a set of attributes and the …

Classification methods are used in machine learning, and pattern recognition. Application of classification includes fraud detection, medical diagnosis, target marketing, etc. The output of …

Classification (Data Mining Book Chapters 5 and 7) • PART ONE: Supervised learning and Classification • Data format: training and test data • Concept, or class definitions and …

In this paper, we present the basic classification techniques. Several major kinds of classification method including decision tree, Bayesian networks, k-nearest neighbour classifier, Neural …

This section describes issues regarding preprocessing the data for classification and prediction. Criteria for the comparison and evaluation of classification methods are also described. …

• Classification: –predicts categorical class labels (discrete or nominal) –classifies data (constructs a model) based on the training set and the values (class labels) in a classifying attribute and …

Find a model for class attribute as a function of the values of other attributes. Goal: previously unseen records should be assigned a class as accurately as possible. – A test set is used to …

Decision Tree Based Classification • Advantages: – Inexpensive to construct – Extremely fast at classifying unknown records – Easy to interpret for small-sized trees – Accuracy is comparable …

In this review article, we discuss a number of different classification algorithms used in data mining for unique applications. There are various techniques to analyse the data for …