Computational algorithm of least absolute deviation method for determining number of outliers under normality.
Jong-Wuu WuWen-Chuan LeePublished in: Appl. Math. Comput. (2006)
Keyphrases
- computational complexity
- computational cost
- high accuracy
- computationally efficient
- improved algorithm
- cost function
- experimental evaluation
- dynamic programming
- preprocessing
- synthetic and real images
- detection algorithm
- objective function
- significant improvement
- clustering method
- noisy data
- detection method
- single pass
- matching algorithm
- tree structure
- high efficiency
- optimization algorithm
- estimation algorithm
- energy function
- segmentation method
- initial set
- support vector machine svm
- segmentation algorithm
- computational efficiency
- k means
- classification method
- memory requirements
- optimization method
- classification algorithm
- recognition algorithm
- reconstruction method
- randomized algorithm
- learning algorithm
- theoretical analysis
- image matching
- outlier removal
- selection algorithm
- method reduces the number
- neural network
- pairwise
- probabilistic model
- cluster centers
- em algorithm
- convergence rate
- input data
- space complexity
- expectation maximization
- search space
- regression model
- random sample consensus
- outlier mining
- kalman filter