List of Tables

Chapter 2. Searching

Table 2.3. Effect of increasing alpha values on the number of iterations for the biz set of web pages

Chapter 3. Creating suggestions and recommendations

Table 3.1. The ratings for the users show that Frank and Constantine agreemore than Frank and Catherine (see also figure 3.2).

Chapter 4. Clustering: grouping things together

Table 4.1. Artificial data for cluster analysis of users that participate in an online community

Table 4.2. The space and time complexity of our clustering algorithms

Chapter 5. Classification: placing things where they belong

Table 5.1. A typical confusion matrix for a simple binary classification problem

Chapter 6. Combining classifiers

Table 6.1. Ten ranges for the attribute Age. This partition is neither too fine nor too coarse; the objective is to adequately represent the various stages of financial developments and risks in a person’s life.

Table 6.2. The range of values for the credit score attribute

Table 6.3. The range of values for the down payment attribute (as percentage of the total loan amount)

Table 6.4. The range of values for the income attribute

Table 6.5. The range of values for the income attribute

Table 6.6. The range of values for the retirement accounts attribute

Table 6.7. The distribution of users, as a percentage of the total number of users, for each class of credit worthiness