One of the main difficulties of SVM is selecting the kernel that transforms the data. The following are the most commonly used transformations:
- Linear
- Polynomial
- Radial basis
- Sigmoid
- Title Page
- Copyright and Credits
- About Packt
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- Preface
- R Fundamentals for Machine Learning
- R and RStudio installation
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- Summary
- Predicting Failures of Banks - Data Collection
- Predicting Failures of Banks - Descriptive Analysis
- Predicting Failures of Banks - Univariate Analysis
- Predicting Failures of Banks - Multivariate Analysis
- Visualizing Economic Problems in the European Union
- Sovereign Crisis - NLP and Topic Modeling
- Other Books You May Enjoy
The SVM kernel parameter
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