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)

Combining models

There are several ways in which models can be combined. We are going to look at each method in this section.

Combining by voting

Let's use an example to understand this method of combining models.

Consider that we have run three models and created a table like this:

We have the confidence for each model and its prediction. Let's see how we can combine these models.

If we take a look at the first row, we can see that each of these models is predicting that a person is going to leave. Hence, if we combine the predictions, we are still predicting that the person is going to leave. The confidence value, or the final confidence, is acquired by adding up the confidence values of all the models and dividing...