Machine learning in medicine. Ton J. Cleophas, Aeilko H. Zwinderman ; with the help from Henny I. Cleophas-Allers. Part three /
"Machine learning is concerned with the analysis of large data and multiple variables. It is also often more sensitive than traditional statistical methods to analyze small data. The first and second volumes reviewed subjects like optimal scaling, neural networks, factor analysis, partial least...
I tiakina i:
| Ngā kaituhi matua: | , |
|---|---|
| Hōputu: | iPukapuka |
| Reo: | English |
| I whakaputaina: |
Dordrecht :
Springer,
[2013]
|
| Ngā marau: | |
| Urunga tuihono: | Springer eBooks |
Rārangi ihirangi:
- Introduction to Machine Learning in Medicine Part Three
- Evolutionary Operations
- Multiple Treatments
- Multiple Endpoints
- Optimal Binning
- Exact P-Values and Their Interpretation
- Probit Regression
- Over-Dispersion
- Random Effects
- Weighted Least Squares
- Multiple Response Sets
- Complex Samples
- Runs Test
- Decision Trees
- Spectral Plots
- Newton’s Methods
- Stochastic Processes: Stationary Markov Chains
- Stochastic Processes: Absorbing Markov Chains
- Conjoint Analysis
- Machine Learning and Unsolved Questions.