The proceedings contain 51 papers. The topics discussed include: Alzheimer’s disease detection and classification: an ensemble machinelearning paradigm;ontology-based car recommender system using functional requirem...
ISBN:
(纸本)9798350303414
The proceedings contain 51 papers. The topics discussed include: Alzheimer’s disease detection and classification: an ensemble machinelearning paradigm;ontology-based car recommender system using functional requirements interaction;data security: a systematic literature review and critical analysis;development of selection method for additional devices to supporting active monitoring of healthcare asset;implementation of the you only look once (YOLO) V5 method for bird pest detection in rice crops;a comparison of oversampling and undersampling methods in sentiment analysis regarding Indonesia fuel price increase using support vector machine;and human resource application development using person-job matching for placement of prospective employees.
The proceedings contain 19 papers. The special focus in this conference is on appliedmachinelearning and data Analytics. The topics include: Blockchain - A Secure and Transparent Solution to Detect Counterfeit Produ...
ISBN:
(纸本)9783031554858
The proceedings contain 19 papers. The special focus in this conference is on appliedmachinelearning and data Analytics. The topics include: Blockchain - A Secure and Transparent Solution to Detect Counterfeit Products;Process Selection for RPA Projects with MDCM: The Case of Izmir Bakircay University;get It Right: Improving Comprehensibility with Adaptable Speech Expression of a Humanoid Service Robot;Benchmarking ML and DL Models for Mango Leaf Disease Detection: A Comparative Analysis;stock Market Prediction with Artificial Intelligence Techniques in Recession Times;sentiment Analysis of Monkeypox Tweets in Latin America;Intensity-Chromaticity-Luminance (ICL) Based Technique for Face Spoofing Detection;AI Insights: Unleashing Financial Distress Signals;optimizing Portfolio for Highly Funded Industries Within Budget Constraints for the Period of 2023–2024;adaptive Neuro Fuzzy-Based Depression Detection Model for Students in Tertiary Education;cassava Syndrome Scan a Pioneering Deep learning System for Accurate Cassava Leaf Disease Classification;self-regulated and Participatory Automatic Text Simplification;preface;Developers’ Perspective on Trustworthiness of Code Generated by ChatGPT: Insights from Interviews;DESI: Diversification of E-Commerce Recommendations Using Semantic Intelligence;aspect-Based Sentiment Classification of Online Product Reviews Using Hybrid Lexicon-machinelearning Approach;forecasting User Payment Behavior Using machinelearning.
The proceedings contain 203 papers. The special focus in this conference is on datascience, machinelearning and Applications. The topics include: A Survey on Stock Market Prediction Using machinelearning Techniques...
ISBN:
(纸本)9789811514197
The proceedings contain 203 papers. The special focus in this conference is on datascience, machinelearning and Applications. The topics include: A Survey on Stock Market Prediction Using machinelearning Techniques;improve the Efficiency of the Classifiers Using Resample Technique on Image Segmentation dataset;Minimization of Deformation of Sensor data with Enhanced Probabilistic Maximum like Hood Selection Process (PMSP);analyzing the Understandability of data Warehouse Conceptual Model Using Fuzzy Logic Techniques;a Survey on Reversible data Hiding Techniques;predictive Analytics in Mining of Educational data: A Research Travelogue;machinelearning and Deep learning in Cyber Security for IoT;K-NN SEMANTIC Inquiry on Scrambled Social Information BASE;a Study on Mining and Analysis of Trajectory databases with Multi-dimensional Feature Sets;Idiom Recommendation Using POS Tagging and Sentence Parsing;Prediction of Housing Prices Using machinelearning, Time Series ARIMA Model and Artificial Neural Network;PRSSDF: Page Rank Specific Student Discussion Forum;a Comparative Study of Recommender Systems;an Overview on Blockchain Technology and Its Applications;Performance Analysis of 8-Bit Vedic Multipliers Using HDL Programming;CMOS Implementation of Comparators for ADCs;capable and Verification Protocol for Restricting Information Storage in Cloud Computing;outlying Info Integrity-Checking Protocol with Augmented Stability to Secure Storage in Cloud;challenges and Uses of Big data Analytics for Social Media;sub-scene Target Detection and Recognition Using Deep learning Convolution Neural Networks;indian and European Script Identification: A Review;ioT Based Garbage Disposer for Educating Rural India;Face Recognition Using Open CV with Deep learning;biometric Recognition Using Fusion.
The proceedings contain 116 papers. The special focus in this conference is on machinelearning, Optimization, and datascience. The topics include: A Generalized Quadratic Loss for SVM and Deep Neural Networks;reliab...
ISBN:
(纸本)9783030645793
The proceedings contain 116 papers. The special focus in this conference is on machinelearning, Optimization, and datascience. The topics include: A Generalized Quadratic Loss for SVM and Deep Neural Networks;reliable Solution of Multidimensional Stochastic Problems Using Metamodels;understanding Production Process Productivity in the Glass Container Industry: A Big data Approach;random Forest Parameterization for Earthquake Catalog Generation;convolutional Neural Network and Stochastic Variational Gaussian Process for Heating Load Forecasting;Explainable AI as a Social Microscope: A Case Study on Academic Performance;policy Feedback in Deep Reinforcement learning to Exploit Expert Knowledge;gradient Bias to Solve the Generalization Limit of Genetic Algorithms Through Hybridization with Reinforcement learning;relational Bayesian Model Averaging for Sentiment Analysis in Social Networks;variance Loss in Variational Autoencoders;wasserstein Embeddings for Nonnegative Matrix Factorization;machinelearning Application to Family Business Status Classification;investigating the Compositional Structure of Deep Neural Networks;optimal Scenario-Tree Selection for Multistage Stochastic Programming;deep 3D Convolution Neural Network for Alzheimer’s Detection;combinatorial Reliability-Based Optimization of Nonlinear Finite Element Model Using an Artificial Neural Network-Based Approximation;CMAC: Clustering Class Association Rules to Form a Compact and Meaningful Associative Classifier;GPU Accelerated data Preparation for Limit Order Book Modeling;can Big data Help to Predict Conditional Stock Market Volatility? An Application to Brexit;importance Weighting of Diagnostic Trouble Codes for Anomaly Detection;Identifying Key miRNA–mRNA Regulatory Modules in Cancer Using Sparse Multivariate Factor Regression;a Krill Herd Algorithm for the Multiobjective Energy Reduction Multi-Depot Vehicle Routing Problem;using Hessians as a Regularization Technique;preface.
The proceedings contain 116 papers. The special focus in this conference is on machinelearning, Optimization, and datascience. The topics include: A Generalized Quadratic Loss for SVM and Deep Neural Networks;reliab...
ISBN:
(纸本)9783030645823
The proceedings contain 116 papers. The special focus in this conference is on machinelearning, Optimization, and datascience. The topics include: A Generalized Quadratic Loss for SVM and Deep Neural Networks;reliable Solution of Multidimensional Stochastic Problems Using Metamodels;understanding Production Process Productivity in the Glass Container Industry: A Big data Approach;random Forest Parameterization for Earthquake Catalog Generation;convolutional Neural Network and Stochastic Variational Gaussian Process for Heating Load Forecasting;Explainable AI as a Social Microscope: A Case Study on Academic Performance;policy Feedback in Deep Reinforcement learning to Exploit Expert Knowledge;gradient Bias to Solve the Generalization Limit of Genetic Algorithms Through Hybridization with Reinforcement learning;relational Bayesian Model Averaging for Sentiment Analysis in Social Networks;variance Loss in Variational Autoencoders;wasserstein Embeddings for Nonnegative Matrix Factorization;machinelearning Application to Family Business Status Classification;investigating the Compositional Structure of Deep Neural Networks;optimal Scenario-Tree Selection for Multistage Stochastic Programming;deep 3D Convolution Neural Network for Alzheimer’s Detection;combinatorial Reliability-Based Optimization of Nonlinear Finite Element Model Using an Artificial Neural Network-Based Approximation;CMAC: Clustering Class Association Rules to Form a Compact and Meaningful Associative Classifier;GPU Accelerated data Preparation for Limit Order Book Modeling;can Big data Help to Predict Conditional Stock Market Volatility? An Application to Brexit;importance Weighting of Diagnostic Trouble Codes for Anomaly Detection;Identifying Key miRNA–mRNA Regulatory Modules in Cancer Using Sparse Multivariate Factor Regression;a Krill Herd Algorithm for the Multiobjective Energy Reduction Multi-Depot Vehicle Routing Problem;using Hessians as a Regularization Technique;preface.
The proceedings contain 44 papers. The topics discussed include: data preprocessing for learning, analyzing and detecting scene text video based on rotational gradient;meteorological forecasting based on big data anal...
ISBN:
(纸本)9781450388382
The proceedings contain 44 papers. The topics discussed include: data preprocessing for learning, analyzing and detecting scene text video based on rotational gradient;meteorological forecasting based on big data analysis;detection of text from video with customized trained anatomy;machinelearning framework for COVID-19 diagnosis;intelligent learning systems for LLL courses intelligent learning systems for LLL courses;fuzzy cross recurrence analysis and tensor decomposition of major-depression time-series data;health care workers’ use of electronic medical information systems: benefits and challenges;and application of electronic health records in polyclinics: barriers & benefits.
The proceedings contain 35 papers. The topics discussed include: implementation of goal-directed design in designing user interface for job seeking website;real-time global sentiment analysis system with custom augmen...
ISBN:
(纸本)9781665437097
The proceedings contain 35 papers. The topics discussed include: implementation of goal-directed design in designing user interface for job seeking website;real-time global sentiment analysis system with custom augmentation of market intelligence;challenges in the implementation of e-learning in Afghanistan higher education;user generated content on twitter to identify market insights: a case study on Zenius;using text mining to improve service quality effort: a case on Indonesia beauty e-commerce;implementation of the spiral optimization algorithm in the support vector machine (SVM) classification method (case study: diabetes prediction);Indonesian marketplace trust analysis using text mining: a case of Tokopedia;and face mask detection using Haar cascade classifier algorithm based on internet of things with telegram bot notification.
The proceedings contain 64 papers. The special focus in this conference is on machinelearning, Optimization, and datascience. The topics include: data Anonymization for Privacy Aware machinelearning;quantitative an...
ISBN:
(纸本)9783030375980
The proceedings contain 64 papers. The special focus in this conference is on machinelearning, Optimization, and datascience. The topics include: data Anonymization for Privacy Aware machinelearning;quantitative and Ontology-Based Comparison of Explanations for Image Classification;conditional Anomaly Detection for Quality and Productivity Improvement of Electronics Manufacturing Systems;federated learning of Deep Neural Decision Forests;active learning Approach for Safe Process Parameter Tuning;on Tree-Based Methods for Similarity learning;modelling Chaotic Time Series Using Recursive Deep Self-organising Neural Networks;determining Principal Component Cardinality Through the Principle of Minimum Description Length;approximating Probabilistic Constraints for Surgery Scheduling Using Neural Networks;on the Role of Hub and Orphan Genes in the Diagnosis of Breast Invasive Carcinoma;vital Prognosis of Patients in Intensive Care Units Using an Ensemble of Bayesian Classifiers;multi-task learning by Pareto Optimality;designing Combinational Circuits Using a Multi-objective Cartesian Genetic Programming with Adaptive Population Size;trading-off data Fit and Complexity in Training Gaussian Processes with Multiple Kernels;a Chained Neural Network Model for Photovoltaic Power Forecast;load Forecasting in District Heating Networks: Model Comparison on a Real-World Case Study;restaurant Health Inspections and Crime Statistics Predict the Real Estate Market in New York City;optimal Trade-Off Between Sample Size and Precision of Supervision for the Fixed Effects Panel data Model;a New Baseline for Automated Hyper-Parameter Optimization;analysing the Overfit of the Auto-sklearn Automated machinelearning Tool;Parameter Optimization of Polynomial Kernel SVM from miniCV;robust Kernelized Bayesian Matrix Factorization for Video Background/Foreground Separation;preface.
In this paper, the main objective is to create an algorithm that uses machinelearning to accurately estimate automobile prices using information about the data model, base anticipated cost, actual price, market price...
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In this paper, the main objective is to create an algorithm that uses machinelearning to accurately estimate automobile prices using information about the data model, base anticipated cost, actual price, market price, and demand. When customers submit the basic specifications of a used automobile, the model can make accurate calculations after testing and training it on a variety of cars and models. Real-time data analysis greatly benefits from machinelearning and datascience, especially with Python, which enables rigorous testing, training, and accurate result generation. This project attempts to highlight how machinelearning can be applied to a simple algorithm and how computers can self-train to create results without tedious programming and the model will be trained by choosing crucial attributes to train the machine literacy model. The model will be trained with a range of machinelearning methods, including Random Forest and Linear Regression Among the performance metrics that will be used to judge the model's effectiveness are perfection, recall, and best position. By altering the model's characteristics and parameters, performance will be improved as well.
Real-world data is often imbalanced, such that the number of training instances varies by class. data augmentation (DA) of under-represented classes is commonly used to improve model generalization in the face of clas...
详细信息
ISBN:
(纸本)9798350364941;9798350364958
Real-world data is often imbalanced, such that the number of training instances varies by class. data augmentation (DA) of under-represented classes is commonly used to improve model generalization in the face of class imbalance. Despite its ubiquity, the impact of data augmentation on machinelearning (ML) models is not clearly understood. Here, we undertake a holistic examination of the effect of DA on under-represented classes. Unlike other studies, which focus on a single ML model type, we examine three different classifier families: convolutional neural networks, support vector machines, and logistic regression models;five different DA techniques and two different data modalities - image and tabular. Our research indicates that DA, when applied to imbalanced data, produces substantial changes in model weights, support vectors and front-end feature selection. These changes occur with respect to all classes, not just the ones that DA is applied to. Further, our empirical analysis shows that data augmentation's positive influence on generalization does not necessarily occur as a result of reducing weight norms. Rather, weight and support vector specialization play important roles in generalization. The specialization process may be a form of memorization that is spawned by variances introduced by augmented data. We investigate the seeming contradiction between improved generalization versus weight and support vector specialization.
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