Book Image

Java for Data Science

By : Richard M. Reese, Jennifer L. Reese
Book Image

Java for Data Science

By: Richard M. Reese, Jennifer L. Reese

Overview of this book

para 1: Get the lowdown on Java and explore big data analytics with Java for Data Science. Packed with examples and data science principles, this book uncovers the techniques & Java tools supporting data science and machine learning. Para 2: The stability and power of Java combines with key data science concepts for effective exploration of data. By working with Java APIs and techniques, this data science book allows you to build applications and use analysis techniques centred on machine learning. Para 3: Java for Data Science gives you the understanding you need to examine the techniques and Java tools supporting big data analytics. These Java-based approaches allow you to tackle data mining and statistical analysis in detail. Deep learning and Java data mining are also featured, so you can explore and analyse data effectively, and build intelligent applications using machine learning. para 4: What?s Inside ? Understand data science principles with Java support ? Discover machine learning and deep learning essentials ? Explore data science problems with Java-based solutions
Table of Contents (19 chapters)
Java for Data Science
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

Working with mean, mode, and median


The mean, median, and mode are basic ways to describe characteristics or summarize information from a dataset. When a new, large dataset is first encountered, it can be helpful to know basic information about it to direct further analysis. These values are often used in later analysis to generate more complex measurements and conclusions. This can occur when we use the mean of a dataset to calculate the standard deviation, which we will demonstrate in the Standard deviation section of this chapter.

Calculating the mean

The term mean, also called the average, is computed by adding values in a list and then dividing the sum by the number of values. This technique is useful for determining the general trend for a set of numbers. It can also be used to fill in missing data elements. We are going to examine several ways to calculate the mean for a given set of data using standard Java libraries as well as third-party APIs.

Using simple Java techniques to find...