Search Results - (( data classification learning algorithm ) OR ( a constructive method algorithm ))
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An efficient and effective case classification method based on slicing
Published 2006“…The paper also discusses two of common classification algorithms that are used either in data mining or in general AI. …”
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An evolutionary based features construction methods for data summarization approach
Published 2015“…Here, feature construction methods are applied in order to improve the descriptive accuracy of the DARA algorithm.This research proposes novel feature construction methods, called Variable Length Feature Construction without Substitution (VLFCWOS) and Variable Length Feature Construction with Substitution(VLFCWS), in order to construct a set of relevant features in learning relational data. …”
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Machine learning for data classification in construction project planning
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Multi-label learning based on positive label correlations using predictive apriori
Published 2019“…Multi-label Learning (MLL) is a general task in data mining that consists of three main tasks: classification, label ranking, and multi-label ranking. …”
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Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)
“…This study developed an algorithm for statistical classification that enable ones to classify a future data to one of predetermined groups based on the measured data which facing two major threats; (i) multicollinearity among the measured variables and (ii) imbalanced groups. …”
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Deep learning for EEG data analysis
Published 2018“…Deep learning (or deep neural network) which enables higher hierarchical representation of complex data has been strongly suggested by a wide range of recent research that these deep architectures of artificial neural network generally outperform the classical EEG feature extraction algorithms or classical EEG classifiers. …”
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization
Published 2021“…Identifying a feature selection method with a classifier algorithm that produces high performance in mortality studies is essential and has not been reported before. …”
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Machine learning application for concrete surface defects automatic damage classification
Published 2024“…Therefore, a Machine Learning classifier for concrete surface defect classification using the Discriminant Analysis Classifier was introduced to more accurately extract the types of concrete surface defects information from the digital images. …”
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Global and local clustering soft assignment for intrusion detection system: a comparative study
Published 2017“…Machine Learning algorithm such as unsupervised learning and supervised learning is capable to solve the problem of classification in IDS. …”
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Data Analysis and Rating Prediction on Google Play Store Using Data-Mining Techniques
Published 2022“…This study aims to predict the ratings of Google Play Store apps using decision trees for classification in machine learning algorithms. The goal of using a Decision Tree is to create a training model that can use to predict the class or value of the target variable by learning simple decision rules inferred from prior data. …”
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A framework of modified adaptive neuro-fuzzy inference engine
Published 2012“…A modified apriori algorithm was employed to reduce the number of clusters effectively on the basis of common data in the clusters of every input to obtain a minimal set of decision rules based on datasets. …”
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APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN
Published 2011“…The Self-Training algorithm greatly benefits semi-supervised learning which allows classification of entities given only a small-size of labelled data. …”
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A systematic review of machine learning techniques and applications in soil improvement using green materials
Published 2023“…A literature review suggests that machine learning algorithms are effective at predicting various soil characteristics, including compressive strength, deformations, bearing capacity, California bearing ratio, compaction performance, stress–strain behavior, geotextile pullout strength behavior, and soil classification. …”
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Cluster identification and separation in the growing self-organizing map: Application in protein sequence classification
Published 2010“…We used simple k-means algorithm as a method to identify clusters in the GSOM. …”
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Segmentation Word to Improve Performance Sentiment Analysis for Indonesian Language
Published 2024“…Subsequently, sentiment analysis classification testing was conducted using both deep learning and machine learning models to assess data quality and accuracy. …”
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Case Slicing Technique for Feature Selection
Published 2004“…One of the problems addressed by machine learning is data classification. Finding a good classification algorithm is an important component of many data mining projects. …”
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Application of target detection method based on convolutional neural network in sustainable outdoor education
Published 2023“…This exploration innovatively proposes a method based on the convolutional neural network (CNN) to mine the target information in underwater camera data. …”
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