"Machine learning" Watermelon book
exercise
- Chapter 1 Introduction
- Chapter 2 model evaluation and selection
- Chapter 3 linear model
- Chapter 4 Decision Tree
- Chapter 5 Neural Networks
- Chapter 6 SVM
Programming Example
- "Machine Learning" Book of watermelon chapter programming examples ( curve, the cost curve is plotted, normalized implement two.)
- "Machine Learning" Book of watermelon chapter programming examples (rate of return (logistic regression) implementation, Comparative fold cross validation and leave a method, Linear Discriminant Analysis ( ) of the implementation.)
- "Machine Learning" Book of watermelon Chapter Programming Example (decision tree algorithm based on dividing the selected entropy, Gini index. Pruning is not pre-pruning, comparison decision tree pruning.)
- "Machine Learning" Book of watermelon chapter programming examples (standard, accumulation algorithm implementation, the handwritten training and prediction data sets, Network to solve XOR problem.)
- "Machine Learning" Book of watermelon
chapter programming examples (
training and the comparison, a linear kernel and the Gaussian kernel is compared with the decision tree,
trained.)
Watermelon data set
Watermelon dataset
book all kinds of watermelon dataset.
Recommended information
- Pumpkin book
strongly recommended !! very useful formula derivation, the learning process can be found read formulas. - Read the back-propagation algorithm (bp algorithm)
Detail algorithm explanation, but the middle " with What is the relationship between "that part wrong, the comments have pointed out, but does not affect the general. - Getting zero-based series of deep learning
to speak quite clearly, it is a good introductory tutorial. - Introduction to popular support vector machine (SVM understanding of the three-state)
entry of choice!