Targeted Learning in Data Science: Causal Inference for Complex Longitudinal Studies (Springer Series in Statistics)
| Author | : | |
| Rating | : | 4.47 (863 Votes) |
| Asin | : | 3319653032 |
| Format Type | : | paperback |
| Number of Pages | : | 440 Pages |
| Publish Date | : | 2014-11-20 |
| Language | : | English |
DESCRIPTION:
Included in Targeted Learning in Data Science are demonstrations with software packages and real data sets that present a case that targeted learning is crucial for the next generation of statisticians and data scientists.. It presents a scientific roadmap to translate real world data science applications into formal statistical estimation problems by using the general template of targeted maximum likelihood estimators to construct targeted machine learning algorithms that incorporate the state-of-the-art in machine learning to estimate quantities of interest, while still providing valid inference. Targeted learning methods within data science are a critical component for answering complex statistical questions in the modern age. Standard methods and s
Included in Targeted Learning in Data Science are demonstrations with software packages and real data sets that present a case that targeted learning is crucial for the next generation of statisticians and data scientists.Provides essential data analysis tools for answering complex big data questions based on real world dataContains machine learning estimators that provide inference within data science Offers applications that demonstrate 1) the translation of the real world application into a statistical estimation problem and 2) the targeted statistical learning methodology