An original non parametric control method is proposed in this paper. A new criterion, UAFWER, defined as the risk of exceeding a pre-set number of false discoveries, is controlled by BS FD, a bootstrap based al
Mallika Rangasamy And Saravanan Venketraman,"An Efficient Statistical Model Based Classification Algorithm For Classifying Cancer Gene Expression Data With Minimal Gene Subsets‖, International Journal Of Cyber Society And Education, Vol. 2, No. 2, Pp.51-66, 2009....
Ideally, a good predictive modeling algorithm would detect linear relationships, nonlinear relationships, interactive relationships, and so on; in other words, it could approximate any relationship between variables. In addition, such algorithms should detect repeatable patterns, and it would be important...
By analyzing the spatial and temporal distribution characteristics of tourist flow in scenic spots, this paper constructs a big data platform based on tourist flow information, and proposes a data mining technology based on the DA-HKRVM algorithm to predict the tourist flow in the dimension of ...
The Relevance Vector Machine (RVM) is another kernel-based algorithm which has not been derived in the context of Statistical Learning Theory; its motivation lies in Bayesian machine learning as discussed in Section 4.8; however, it has exactly the same functional form as the SVM. The basic mot...
the random start values can be directly input into the model and the results can be compared to the best fitting LL model. This is useful because if different start values produce dramatically different results, this might suggest that the algorithm converged at a local maxima instead of global...
Feature Selection:Genetic Algorithm based Feature Selection, Ensemble Learning based Feature Selection, TreeSHAP, Signal Noise ratio, Sum Squares ratio. Clustering:BIRCH, CLARANS, DBSCAN, DENCLUE, Deterministic Annealing, K-Means, X-Means, G-Means, Neural Gas, Growing Neural Gas, Hierarchical Clusterin...
December 25, 2019December 27, 2019 statcompute Data MiningPNNR Improve General Regression Neural Network by Monotonic Binning A major criticism on the binning algorithm as well as on the WoE transformation is that the use of binned predictors will decrease the model predictive power due to the...
Feature Selection:Genetic Algorithm based Feature Selection, Ensemble Learning based Feature Selection, TreeSHAP, Signal Noise ratio, Sum Squares ratio. Clustering:BIRCH, CLARANS, DBSCAN, DENCLUE, Deterministic Annealing, K-Means, X-Means, G-Means, Neural Gas, Growing Neural Gas, Hierarchical Clusterin...
FreeSurfer used for segmentation brightness information of the voxels and local geometric information in order to label the voxels (Dale et al., 1999). FSL based on a hidden Markov random field model and an associated expectation maximisation algorithm for tissue segmentation (Zhang et al., 2001)...