Data mining for business analytics concepts, techniques, and applications in Python
"This book supplies insightful, detailed guidance on fundamental data mining techniques. The book guides readers through the use of Python software for developing predictive models and techniques in order to describe and find patterns in data. The authors use interesting, real-world examples to...
| Otros Autores: | , , |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Hoboken, N. J.:
Wiley
2020.
Hoboken, New Jersey : [2020] |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009849080606719 |
Tabla de Contenidos:
- Foreword / by Gareth James
- Foreword / by Ravi Bapna
- Preface to the Python edition
- Overview of the data mining process
- Data visualization
- Dimension reduction
- Evaluating predictive performance
- Multiple linear regression
- k-nearest neighbors (kNN)
- The naive Bayes classifier
- Classification and regression trees
- Logistic regression
- Neural nets
- Discriminant analysis
- Combining methods : ensembles and uplift modeling
- Association rules and collaborative filtering
- Cluster analysis
- Handling time series
- Regression-based forecasting
- Smoothing methods
- Social network analytics
- Text mining
- Cases.
