Evaluating the impact of data quantity, distribution and algorithm selection on the accuracy of 3D subsurface models using synthetic grid models of varying complexity.
Kelsey E. MacCormackJason J. BrodeurCarolyn H. EylesPublished in: J. Geogr. Syst. (2013)
Keyphrases
- probabilistic model
- computational cost
- high accuracy
- incomplete data
- experimental data
- data distribution
- noisy data
- easily interpretable
- computational complexity
- learned models
- historical data
- worst case
- data sets
- input data
- synthetic datasets
- data analysis
- optimal solution
- data points
- selection algorithm
- expectation maximization
- surface meshes
- parameter estimates
- parametric models
- data reduction
- classification trees
- np hard
- decision trees
- training data
- dynamic programming
- detection algorithm
- clustering method
- simulated annealing
- probability distribution
- classification accuracy
- space complexity
- parameter estimation
- missing data
- k means
- search space
- high dimensional
- objective function
- accurate models
- large scale data sets