Learn Data Mining Through Excel: A Step-by-Step Approach for Understanding Machine Learning Methods, 2nd Edition

Use popular data mining techniques in Microsoft Excel to better understand machine learning methods. Most software tools and programming language packages take data input and deliver data mining results directly, presenting no insight on working mechanics and creating a chasm between input and output. This is where Excel can help, and this book will show you exactly how. This updated edition demonstrates how to work with data in a transparent manner using Excel. When you open an Excel file, data is visible immediately and you can work with it directly. You'll see how to examine intermediate results even as you are still conducting your mining task, offering a deeper understanding of how data is manipulated, and results are obtained. These are critical aspects of the model construction process that are often hidden in software tools and programming language packages. Over the course of Learn Data Mining Through Excel , you will learn the data mining advantages the application offers when the data sets are not too large. You'll see how to use Excel's built-in features to create visual representations of your data, enabling you to present your findings in an accessible format. Author Hong Zhou walks you through each step, offering not only an active learning experience, but teaching you how the mining process works and how to find hidden patterns within the data. Upon completing this book, you will have a thorough understanding of how to use an application you very likely already have to mine and analyze data, and how to present results in various formats. What You Will Learn Comprehend data mining using a visual step-by-step approach Gain an introduction to the fundamentals of data mining Implement data mining methods in Excel Understand machine learning algorithms Leverage Excel formulas and functions creatively Obtain hands-on experience with data mining and Excel Who This Book Is For Anyone who is interested in learning data mining or machine learning, especially data science visual learners and people skilled in Excel who would like to explore data science topics and/or expand their Excel skills. A basic or beginner level understanding of Excel is recommended. Table of Contents 5 About the Author 9 About the Technical Reviewer 10 Chapter 1: Excel and Data Mining 11 Why Excel? 11 Why the Second Edition? 15 Prepare Some Excel Skills 17 Formula 17 Autofill or Copy 18 Absolute Reference 19 Paste Special and Paste Values 22 IF Function Series 24 Reinforcement Exercises 31 Review Points 31 Chapter 2: Linear Regression 32 General Understanding 32 Learn Linear Regression Through Excel 36 Learn Multiple Linear Regression Through Excel 39 Reinforcement Exercises 43 Review Points 44 Chapter 3: K-Means Clustering 45 General Understanding 45 Learn K-Means Clustering Through Excel 46 Reinforcement Exercises 59 Review Points 60 Chapter 4: Linear Discriminant Analysis 61 General Understanding 61 Solver 63 Learn LDA Through Excel 67 Reinforcement Exercises 78 Review Points 78 Chapter 5: Cross-Validation and ROC 79 General Understanding of Cross-Validation 79 Learn Cross-Validation Through Excel 80 General Understanding of ROC Analysis 85 Learn ROC Analysis Through Excel 87 Reinforcement Exercises 92 Review Points 93 Chapter 6: Logistic Regression 94 General Understanding 94 Learn Logistic Regression Through Excel 96 By Means of Maximizing Log Likelihoods 97 By Means of Minimizing Log Losses 104 Reinforcement Exercises 107 Review Points 108 Chapter 7: K-Nearest Neighbors 109 General Understanding 109 Learn K-NN Through Excel 110 Experiment 1 111 Experiment 2 114 Experiment 3 119 Experiment 4 124 Reinforcement Exercises 126 Review Points 126 Chapter 8: Hierarchical Clustering and Dendrogram 127 General Understanding 127 Draw a Dendrogram in Excel Without Add-ins 129 Learn Hierarchical Clustering Through Excel 135 Reinforcement Exercises 147 Review Points 148 Chapter 9: Naive Bayes Classification 149 General Understanding 149 Learn Naïve Bayes Through Excel 154 Exercise 1 154 Exercise 2 158 Reinforcement Exercises 165 Review Points 165 Chapter 10: Decision Trees 166 General Understanding 167 Learn Decision Trees Through Excel 170 Learn Decision Trees Through Excel 171 A Better Approach 183 Apply the Model 187 Reinforcement Exercises 190 Review Points 190 Chapter 11: EDA, Data Cleaning, and Feature Selection 191 Learn Exploratory Data Analysis Through Excel 191 Learn Data Cleaning Through Excel 200 Feature Selection 204 Normalization and Standardization 205 Correlation 208 Learn Feature Selection Through Excel 209 Reinforcement Exercises 213 Review Points 213 Chapter 12: Association Analysis 215 General Understanding 215 Learn Association Analysis Through Excel 218 Reinforcement Exercises 226 Review Points 227 Chapter 13: Artificial Neural Network 228 General Understanding 228 Learn Neural Network Through Excel 230 Experiment 1 230 Experiment 2 242 Reinforcement Exercises 254 Review Points 254 Chapter 14: Text Mining 256 General Understanding 256 Learn Text Mining Through Excel 258 Word Embedding and ChatGPT 275 Reinforcement Exercises 277 Review Points 277 Chapter 15: After Excel 279 Index 282 df-Capture.PNG 1