Machine Learning techniques are a vital part of IoT, which deals with an automatic prediction for predictive maintenance systems. ML allows automated fault diagnosis and prognosis for various types of equipment. In this study, Majority Voting Machine Learning approach demonstrated for fault diagnosis of...
In this paper we demonstrate how weighted majority voting with multiplicative weight updating can be applied to obtain robust algorithms for learning binary relations. We first present an algorithm that obtains a nearly optimal mistake bound but at the expense of using exponential computation to make ...
Table 6. Phase-I (Normal vs. Abnormal) classification performance of different supervised models and majority voting algorithm using the validation set. (Abbreviations: SVM: Support Vector Machine, DT: Decision Tree, KNN: k-Nearest Neighbor, NB: Naïve Bayes, ANN: Artificial Neural Network, STD...
A simple and effective method, based on weighted voting, is introduced for constructing a compound algorithm in such a circumstance. We call this method the Weighted Majority Algorithm. We show that this algorithm is robust in the presence of errors in the data. We discuss various versions of ...
The results of this study lead me to believe that for some voting methods in my algorithm, perturbing on K values can offer significant improvement. This especially seems to be the case with the first three voting methods, which are all forms of majority voting. ...
Finally, we devise a decision tree algorithm and a weighted majority voting algorithm based two-dimensional region rules to aggregate predictors and generate interpretable rules. This is also a data fusion process. The method is illustrated... Y Hamuro,N Katoh,IH Edward,... - Springer Berlin ...
MACHINE learningPLURALITY votingCROWNS (Botany)VOTING machinesLIGHT absorptionThe shape and area of the crown of each tree are among the most influential parameters for identifying and controlling the processes of photosynthesis, respiration, transpiration and its...
The special majority voting algorithm is proposed and used for raising an alarm of upcoming seizure. EEG signals are denoised using MSPCA (Multiscale PCA), the features were extracted by WPD (wavelet packet decomposition), and EEG signals were classified using Rotation Forest. The significan...
Kim, H., Kim, H., Moon, H., Ahn, H.: A weight-adjusted voting algorithm for ensembles of classifiers. J. Korean Stat. Soc.40(4), 437–449 (2011) ArticleMathSciNetGoogle Scholar King, R.D., Feng, C., Sutherland, A.: Statlog: comparison of classification algorithms on large real...
Differential evolution algorithm as a tool for optimal feature subset selection in motor imagery EEG. Expert Syst Appl. 2017;90:184–95. https://doi.org/10.1016/j.eswa.2017.07.033. Article Google Scholar Kumar S, Sharma A, Tsunoda T. An improved discriminative filter bank selection approach ...