A confusion matrix is a table used to describe the performance of a classification model. It is run on a test dataset for which the truth values are known. This is how we arrive at things such as the following.
- Title Page
- Copyright and Credits
- Packt Upsell
- Contributors
- Preface
- Machine Learning Basics
- Introduction to machine learning
- Data mining
- Artificial Intelligence
- Bio-AI
- Deep learning
- Probability and statistics
- Approaching your machine learning project
- Iris dataset
- Supervised learning
- Unsupervised learning
- Reinforcement learning
- Build, buy, or open source
- Additional reading
- Summary
- References
- ReflectInsight – Real-Time Monitoring
- Bayes Intuition – Solving the Hit and Run Mystery and Performing Data Analysis
- Risk versus Reward – Reinforcement Learning
- Fuzzy Logic – Navigating the Obstacle Course
- Color Blending – Self-Organizing Maps and Elastic Neural Networks
- Facial and Motion Detection – Imaging Filters
- Encyclopedias and Neurons – Traveling Salesman Problem
- Should I Take the Job – Decision Trees in Action
- Deep Belief – Deep Networks and Dreaming
- Microbenchmarking and Activation Functions
- Intuitive Deep Learning in C# .NET
- Quantum Computing – The Future
Confusion matrix
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