The proposed algorithm is named the KNN Ameliorated Tree Seed Algorithm (KATSA). First, based on the current best tree, the search space is divided into best and non-best neighbor areas by the KNN mechanism. Based on this division approach, the proposed seed generation strategy has a precise...
Fast superresolution frequency detection using MUSIC algorithm audio music frequency dtmf signal-processing dsp voip spectral-analysis audio-processing frequency-analysis frequency-estimation doa spectral-methods dtmf-detector eigen-vector-decomposition spectral-method doa-estimation eigenvalueproblems amplitude-es...
The evaluation method used in the algorithm is the wrapper method, designed to keep a degree of balance between two objectives: (i) minimize the number of selected features, (ii) maintain a high level of accuracy. We use the k-nearest-neighbor (KNN) machine learning algorithm in the ...
The performance of the proposed algorithm is evaluated on different datasets and compared with three state-of-the-art boosting algorithms, k-Nearest Neighbor (KNN) and Support Vector Machine (SVM). The results show that the performance of the proposed algorithm ranks first in all but one dataset...
For this prediction task, we propose a simple learning strategy based on kNN. Let p1,...,ps be the training parameters. During training, the instances I(p1),...,I(ps) are solved usingAlgorithm 1, where the initial hints are set toRELAXfor all constraints. During the solution of each ...
SARSA (State-Action-Reward-State-Action) algorithm Temporal difference learning Data Mining Algorithms C4.5 k-Means SVM (Support Vector Machine) Apriori EM (Expectation-Maximization) PageRank AdaBoost KNN (K-Nearest Neighbors) Naive Bayes CART (Classification and Regression Trees) Deep Learning archite...
In computer science, divide and conquer [11] is an algorithm design paradigm based on multi-branched recursion and a tree structure. By recursively dividing a problem into two or more sub-problems, the original problem can be made sufficiently simple to be solved in the sub-problems. Then, ...
It is noticeable that the research on an inertial iterative algorithm is still unexplored on a Banach space. Inspired by the work in [20, 30, 32], we establish an inertial hybrid iterative algorithm in- volving Bregman relatively nonexpansive mapping to find a common solution of GEP(1.1) ...
In Ibrahim et al. [27], the Harris-Hawks optimizer was modified for feature selection and the support vector machine as an object function. The authors propose a hybrid strategy based on the Harris-Hawk optimization (HHO) algorithm to optimize the parameters of the SVM model and find the opt...
V-shaped transfer functions for ant lion optimization algorithm in feature selection problem. In: Proceedings of the international conference on future networks and distributed systems, pp 1–7 Papa JP, Rosa GH, de Souza AN et al (2018) Feature selection through binary brain storm optimization. ...