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Data Forecasting and Segmentation Using Microsoft Excel

You're reading from   Data Forecasting and Segmentation Using Microsoft Excel Perform data grouping, linear predictions, and time series machine learning statistics without using code

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Product type Paperback
Published in May 2022
Publisher Packt
ISBN-13 9781803247731
Length 324 pages
Edition 1st Edition
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Author (1):
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Fernando Roque Fernando Roque
Author Profile Icon Fernando Roque
Fernando Roque
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Table of Contents (19) Chapters Close

Preface 1. Part 1 – An Introduction to Machine Learning Functions
2. Chapter 1: Understanding Data Segmentation FREE CHAPTER 3. Chapter 2: Applying Linear Regression 4. Chapter 3: What is Time Series? 5. Part 2 – Grouping Data to Find Segments and Outliers
6. Chapter 4: Introduction to Data Grouping 7. Chapter 5: Finding the Optimal Number of Single Variable Groups 8. Chapter 6: Finding the Optimal Number of Multi-Variable Groups 9. Chapter 7: Analyzing Outliers for Data Anomalies 10. Part 3 – Simple and Multiple Linear Regression Analysis
11. Chapter 8: Finding the Relationship between Variables 12. Chapter 9: Building, Training, and Validating a Linear Model 13. Chapter 10: Building, Training, and Validating a Multiple Regression Model 14. Part 4 – Predicting Values with Time Series
15. Chapter 11: Testing Data for Time Series Compliance 16. Chapter 12: Working with Time Series Using the Centered Moving Average and a Trending Component 17. Chapter 13: Training, Validating, and Running the Model 18. Other Books You May Enjoy

Grouping with the K-means machine learning function

We need a machine learning classification algorithm because classifying a large amount of data is very difficult using traditional business intelligence tools such as pivot tables and charts. We will review and analyze two cases of a large amount of data:

  • Sales in multiple countries and regions
  • Absentees in the office due to different diseases in human resources

We'll inquire about the results of grouping this data with the classification and grouping algorithm, K-means. Then, we will look at the basic concepts of grouping for single- and multiple-variable classifications. This knowledge is important because we will apply these terms to calculate the groups using the Excel add-in K-means function in the next chapter.

As it is difficult to classify large amounts of data, the following segregations are used:

  • Revenue per country
  • Absent hours per disease and month

The challenges of doing...

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