As we all know, when Pearson correlation analysis is performed between a gene and ME of its corresponding module, the absolute value of the PCC is called the module membership (MM) of this gene13. In an ideal situation, genes in the same module should be highly correlated. That is, if ...
public static HashingAlgorithm fromString(String name) Creates or finds a HashingAlgorithm from its string representation. Parameters: name - a name to look for. Returns: the corresponding HashingAlgorithm.values public static Collection values() Gets known HashingAlgorithm values. Returns: known Hashi...
The whale optimization algorithm has received much attention since its introduction due to its outstanding performance. However, like other algorithms, the whale optimization algorithm still suffers from some classical problems. To address the issues of slow convergence, low optimization precision, and sus...
public static EncryptionAlgorithm fromString(String name) Creates or finds a EncryptionAlgorithm from its string representation. Parameters: name - a name to look for. Returns: the corresponding EncryptionAlgorithm.values public static Collection values() Gets known EncryptionAlgorithm values. Returns: k...
We describe the maximum-likelihood parameter estimation problem and how the Expectation- Maximization (EM) algorithm can be used for its solution. We first describe theform of the EM algorithm as it is often given in the literature. We then develop the EM pa- rameter estimation procedure for ...
Table 23.2 presented definition of the evaluation measure and its formula. Prior to doing this, the study applied a technique called Confusion Matrix to summarize the performance of classification algorithms because an unequal observation or more than two classes in dataset may mislead the result. ...
BiteOpt can successfully solve MOO problems via direct optimization of hypervolume of a set of points. This approach requires a hypervolume tracker which keeps track of a certain number of improving solutions, and updates its state (and hypervolume estimate) on each objective function evaluation (opt...
To the OS a GPU appears as a device, and its installed drivers manage the execution of work on this device. The OS and the GPU drivers work together to help complete the tasks. At the lowest level, a sequence of commands is sent to the GPU device through its command queues. The ...
In the designer, creating and using a machine learning model is typically a three-step process: Configure a model, by choosing a particular type of algorithm, and then defining its parameters or hyperparameters. Provide a dataset that's labeled and has data compatible with the algorithm. Connect...
Once these parameters are determined, we have a quantum circuit to produce this state—which we call the VQE ground state below—and can perform measurements to determine its properties. We found that BayesMGD was able to converge on parameters corresponding to the VQE ground state within a ...