November 2006
Beginner to intermediate
292 pages
7h 26m
English
book
Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining
by Glenn J. Myatt
Content preview from Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.
7.7 SUMMARY
Types of models:
- Classification: Models where the response variable is categorical. These are assessed using: concordance, error rate, specificity, and sensitivity analysis.
Table 7.20. Summary of predictive modeling approaches in this chapter
- Regression: Models where the response variable is continuous. These are assessed using r2 and residual analysis.
Building a prediction model involves the following steps:
- Select methods based on problem
- Separate out training and test sets
- Optimize the models
- Assess models generated
Applying a prediction model follows these steps:
- Evaluate whether an observation can be used with the model
- Present observations to model
- Combine results from multiple models (if appropriate)
- Understand confidence and/or explain how results were computed
Table 7.20 summarizes the different methods described in this chapter.
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Read now
Unlock full access
More than 5,000 organizations count on O’Reilly
O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.