Stacking takes the outputs of machine learning estimators and then uses those as inputs for another algorithm. You can, of course, feed the output of the higher-level algorithm to another predictor. It is possible to use any arbitrary topology, but for practical reasons you should try a simple setup first as also dictated by Occam's razor.
- Credits
- Preface
- Getting Started with Python and Machine Learning
- What is machine learning and why do we need it?
- A very high level overview of machine learning
- A brief history of the development of machine learning algorithms
- Generalizing with data
- Overfitting, underfitting and the bias-variance tradeoff
- Avoid overfitting with feature selection and dimensionality reduction
- Preprocessing, exploration, and feature engineering
- Combining models
- Installing software and setting up
- Troubleshooting and asking for help
- Summary
- Exploring the 20 Newsgroups Dataset with Text Analysis Algorithms
- Spam Email Detection with Naive Bayes
- News Topic Classification with Support Vector Machine
- Click-Through Prediction with Tree-Based Algorithms
- Click-Through Prediction with Logistic Regression
- Stock Price Prediction with Regression Algorithms
- Best Practices
- Machine learning workflow
- Best practices in the data preparation stage
- Best practices in the training sets generation stage
- Best practice 5 - determine categorical features with numerical values
- Best practice 6 - decide on whether or not to encode categorical features
- Best practice 7 - decide on whether or not to select features and if so, how
- Best practice 8 - decide on whether or not to reduce dimensionality and if so how
- Best practice 9 - decide on whether or not to scale features
- Best practice 10 - perform feature engineering with domain expertise
- Best practice 11 - perform feature engineering without domain expertise
- Best practice 12 - document how each feature is generated
- Best practices in the model training, evaluation, and selection stage
- Best practices in the deployment and monitoring stage
- Summary
Stacking
-
No Comment
..................Content has been hidden....................
You can't read the all page of ebook, please click here login for view all page.