Machine learningRule strengthSmart systemsSemi-supervised learningIt has become essential to develop machine learning techniques due to the automation of various tasks. At present, several tasks need manual intervention for better reliability of the system. In this work, fuzzy-based approach has been ...
System Construction of Mind Map in English Vocabulary Teaching Based on Machine Learning Algorithm. Mobile Information Systems, 2022, 2022: 7775528. DOI:10.1155/2022/7775528 141. Yi, Y., Zhang, W., Xu, X. et al. Evaluation of neural network models for landslide susceptibility assessment. ...
The machine learning cluster is presented with the biggest bubble in comparison to the other clusters on the map, which indicates the biggest research interest and contribution to this topic. Support vector machine is a machine learning algorithm and is separated in a different cluster, placed into...
Substituted letter: “storl” →“storm” Spelling distance (Damerau–Levenshtein distance) algorithm Algolia’s typo tolerance algorithm is based on distance, following theDamerau–Levenshtein distancealgorithm. Distance refers to the difference in spelling between a typed word and its exact match in th...
GENIE: a hybrid genetic algorithm for feature classification in multispectral images Genetic algorithmsImage processingMachine learningNeural networksRoadsWe consider the problem of pixel-by-pixel classification of a multi- spectral image using ... SJ Perkins,JP Theiler,SP Brumby,... - Applications &...
The FCM clustering algorithm is a powerful unsupervised learning technique to form a few rules with simple and interpretable structure5. FCM induces rules by organizing and categorizing data into partitions. Partitions with homogeneous data form clusters, and each cluster is associated with a rule. Th...
ANNs includes weights between neurons (nodes) that can be changed with respect to a machine learning algorithm by using a suitable cost function to learn from the observed data in order to improve the model. ANNs consists of many layers, in which the first layer represents an input layer, ...
First of all, yes indeed the model is overfitted. There was a slight increase in accuracy between the standard and my proposed algorithm test result, though the validation accuracy did not support the same outcome. Nonetheless, when it comes to machine learning analysis, there are lots of thin...
The paper presents the research of learning algorithm of FNN.In the algorithm,based on separated-layer training,the method trains network through changing numbers of hidden-layer points and training samples,and factors of BP algorithm.The method can simplify the structure of network and reduce the ...
Naïve Bayes mechanism is widely accepted for its fast supervised learning algorithm in data mining which offers reasonable results in large-scale prediction of difficult datasets. However, the main drawback is that it needs independence of criteria (Bui Tien et al., 2012). For comparing three ...