Feature selection and extraction
... ■ According to the success of the model for individual feature subsets, it is chosen which subsets will be tested in the next iteration. ■ Feature selection is here part of the model training; we need separate testing data to evaluate the final model error. ...
... ■ According to the success of the model for individual feature subsets, it is chosen which subsets will be tested in the next iteration. ■ Feature selection is here part of the model training; we need separate testing data to evaluate the final model error. ...
Meshless Local Petrov-Galerkin Mixed Collocation Steady-State Heat Transfer
... Recently, simple non-iterative methods have been under development for solving inverse problems without using the primal symmetric weak-form: with global RBF as the trial function, collocation of the differential equation and boundary conditions leads to the global primal RBF collocation method [Che ...
... Recently, simple non-iterative methods have been under development for solving inverse problems without using the primal symmetric weak-form: with global RBF as the trial function, collocation of the differential equation and boundary conditions leads to the global primal RBF collocation method [Che ...
Natural rules for Arabidopsis thaliana
... analysis showed the same results in both 5’ and 3’ splicing sites with the number of U in intron flank region larger than in exon flank region. This result was reversed for A, G, and C (Figure 2). Statistical analysis showed that there were significant differences in all four types of nucleotides wi ...
... analysis showed the same results in both 5’ and 3’ splicing sites with the number of U in intron flank region larger than in exon flank region. This result was reversed for A, G, and C (Figure 2). Statistical analysis showed that there were significant differences in all four types of nucleotides wi ...
March 26, 2013 Palmetto Lecture on Comparative Inference
... Example: Suppose that the observed data in an experiment of interest is a binomial random variable with distribution X ∼ B(n, p1 + p2 ) , where p1 ≥ 0, p2 ≥ 0 and 0 ≤ p1 + p2 ≤ 1. The model would be appropriate in situations in which there are two mutually exclusive causes of “success” in a sequence ...
... Example: Suppose that the observed data in an experiment of interest is a binomial random variable with distribution X ∼ B(n, p1 + p2 ) , where p1 ≥ 0, p2 ≥ 0 and 0 ≤ p1 + p2 ≤ 1. The model would be appropriate in situations in which there are two mutually exclusive causes of “success” in a sequence ...
ASSESSING AND N. MITNE-284
... Summary of Results From the above discussion, it can be seen that current plant analysis methods for determining reliability are not completely suited for analyzing components. This report presents a potential approach for extending these methods. The approach employs conventional reliability analys ...
... Summary of Results From the above discussion, it can be seen that current plant analysis methods for determining reliability are not completely suited for analyzing components. This report presents a potential approach for extending these methods. The approach employs conventional reliability analys ...
Exact discovery of length-range motifs
... The inputs to the algorithm are the time series x, its total length T , motif length L, and the number of reference points Nr . The algorithm starts by selecting a random set of Nr reference points. The algorithm works in two phases: The first phase (called hereafter referencing phase) is used to c ...
... The inputs to the algorithm are the time series x, its total length T , motif length L, and the number of reference points Nr . The algorithm starts by selecting a random set of Nr reference points. The algorithm works in two phases: The first phase (called hereafter referencing phase) is used to c ...
Constant-Time Local Computation Algorithms
... existing algorithm for a graph problem that does not appear to be implementable as an LCA, and “weaken” it in some sense (running time, approximation ratio, etc.) The resulting algorithm, while weaker, can be implemented (usually in a straightforward fashion) as an LCA. We focus on the following pro ...
... existing algorithm for a graph problem that does not appear to be implementable as an LCA, and “weaken” it in some sense (running time, approximation ratio, etc.) The resulting algorithm, while weaker, can be implemented (usually in a straightforward fashion) as an LCA. We focus on the following pro ...
1 managing long linked lists using lock free techniques
... implemented using either blocking or non-blocking/lock-free synchronization. Blocking synchronization is popular because it is familiar and also amenable to worst-case performance analysis (important for certain real time applications). Unfortunately it also suffers from some undesirable characteris ...
... implemented using either blocking or non-blocking/lock-free synchronization. Blocking synchronization is popular because it is familiar and also amenable to worst-case performance analysis (important for certain real time applications). Unfortunately it also suffers from some undesirable characteris ...
the method of a two-level text-meaning similarity
... applying the results for particular objectives. Different options of various realizations of words calculation and the further results processing create a wide specter of methods and algorithms, suggested in this class. From the other hand, clustering problem solving, especially in the context of it ...
... applying the results for particular objectives. Different options of various realizations of words calculation and the further results processing create a wide specter of methods and algorithms, suggested in this class. From the other hand, clustering problem solving, especially in the context of it ...
Unsupervised Feature Selection for the k
... iterative expectation-maximization type approach, which attempts to address the following objective: given a set of points in a Euclidean space and a positive integer k (the number of clusters), split the points into k clusters so that the total sum of the (squared Euclidean) distances of each point ...
... iterative expectation-maximization type approach, which attempts to address the following objective: given a set of points in a Euclidean space and a positive integer k (the number of clusters), split the points into k clusters so that the total sum of the (squared Euclidean) distances of each point ...
Sequence of Real Numbers
... sequences .If is a limit ordinal and X is a set; an -indexed sequences of elements of X is a function from to X. In this terminology a w-indexed sequence is an ordinary sequence ...
... sequences .If is a limit ordinal and X is a set; an -indexed sequences of elements of X is a function from to X. In this terminology a w-indexed sequence is an ordinary sequence ...
38. A preconditioner for the Schur complement domain
... with successive and multiple right-hand sides. This technique is based on the exploitation of previously computed conjugate directions. Figure 5.2 shows the iteration history with respect to the number of right-hand sides using different methods, and we report also the total number of iterations, the ...
... with successive and multiple right-hand sides. This technique is based on the exploitation of previously computed conjugate directions. Figure 5.2 shows the iteration history with respect to the number of right-hand sides using different methods, and we report also the total number of iterations, the ...
Shortest Paths in Directed Planar Graphs with Negative Lengths: a
... The structure of our algorithm is different—it is a simple divide-and-conquer, in which the recursive problem is the same as the original problem, single-source shortest-path distances. In addition, we require no data structures aside from the dynamic-tree data structure used in [Klein 2005] and a b ...
... The structure of our algorithm is different—it is a simple divide-and-conquer, in which the recursive problem is the same as the original problem, single-source shortest-path distances. In addition, we require no data structures aside from the dynamic-tree data structure used in [Klein 2005] and a b ...
Kernel Estimation and Model Combination in A Bandit Problem with
... problem in more flexible settings is recently studied under a minimax framework (Goldenshluger and Zeevi, 2009; Goldenshluger and Zeevi, 2013). Empirical studies are also reported for parametric UCB-type algorithms (e.g., Li et al., 2010). The regret analysis of a special linear setting is given in ...
... problem in more flexible settings is recently studied under a minimax framework (Goldenshluger and Zeevi, 2009; Goldenshluger and Zeevi, 2013). Empirical studies are also reported for parametric UCB-type algorithms (e.g., Li et al., 2010). The regret analysis of a special linear setting is given in ...
A model for codon position bias in RNA editing
... This evolutionary model, when applied to plant mitochondrial genes, does not predict the correct preference in the codon positions for editing. Instead, it still predicts the majority of editing sites to occur at the third codon position. This suggests that in plant mitochondrial genes editing event ...
... This evolutionary model, when applied to plant mitochondrial genes, does not predict the correct preference in the codon positions for editing. Instead, it still predicts the majority of editing sites to occur at the third codon position. This suggests that in plant mitochondrial genes editing event ...
Portfolio Value-at-Risk Using Regular Vine Copulas
... We will now introduce the main categories of methods used to evaluate risk, as well as briefly analyze them in terms of the properties of coherent risk measure and discuss the advantages and disadvantages of each method (McNeil et al. (2005), p. 34-36). Notional-amount approach. Risk of portfolio is ...
... We will now introduce the main categories of methods used to evaluate risk, as well as briefly analyze them in terms of the properties of coherent risk measure and discuss the advantages and disadvantages of each method (McNeil et al. (2005), p. 34-36). Notional-amount approach. Risk of portfolio is ...