Book Image

Machine Learning for Data Mining

By : Jesus Salcedo
Book Image

Machine Learning for Data Mining

By: Jesus Salcedo

Overview of this book

Machine learning (ML) combined with data mining can give you amazing results in your data mining work by empowering you with several ways to look at data. This book will help you improve your data mining techniques by using smart modeling techniques. This book will teach you how to implement ML algorithms and techniques in your data mining work. It will enable you to pair the best algorithms with the right tools and processes. You will learn how to identify patterns and make predictions with minimal human intervention. You will build different types of ML models, such as the neural network, the Support Vector Machines (SVMs), and the Decision tree. You will see how all of these models works and what kind of data in the dataset they are suited for. You will learn how to combine the results of different models in order to improve accuracy. Topics such as removing noise and handling errors will give you an added edge in model building and optimization. By the end of this book, you will be able to build predictive models and extract information of interest from the dataset
Table of Contents (7 chapters)

Demonstrating a neural network

Let's jump to a hands-on example of neural networks. The software that we are using is the SPSS Modeler, provided by IBM. But feel free to use any data-mining software package.

Running a neural network model

In order to run our first neural network, we will have to bring in the data that we will be using, if you are using IBM SPSS Modeler you can follow these steps:

  1. Get the data using the Var. File node, and bring it up to the canvas:
  1. Attach the dataset to the source node:

Click on the triple dot box on the right side of file box and navigate to your data; we are using Electronics_Data here:

Click Open.

  1. Go on to the Types tab to check whether the data was read correctly:

Click...