Handbook of Machine Learning for Computational Optimization
portes grátis
Handbook of Machine Learning for Computational Optimization
Applications and Case Studies
Jain, Vishal; Kannan, Ramani; Juneja, Abhinav; Juneja, Sapna
Taylor & Francis Ltd
11/2021
280
Dura
Inglês
9780367685423
15 a 20 dias
535
Descrição não disponível.
Chapter 1 Random Variables in Machine Learning Chapter 2 Analysis of EMG Signals using Extreme Learning Machine with Nature Inspired Feature Selection Techniques Chapter 3 Detection of Breast Cancer by Using Various Machine Learning and Deep Learning Algorithms Chapter 4 Assessing the Radial Efficiency Performance of Bus Transport Sector Using Data Envelopment Analysis Chapter 5 Weight-Based Codes-A Binary Error Control Coding Scheme-A Machine Learning Approach Chapter 6 Massive Data Classification of Brain Tumors Using DNN: Opportunity in Medical Healthcare 4.0 through Sensors Chapter 7 Deep Learning Approach for Traffic Sign Recognition on Embedded Systems Chapter 8 Lung Cancer Risk Stratification Using ML and AI on Sensor- Based IoT: An Increasing Technological Trend for Health of Humanity Chapter 9 Statistical Feedback Evaluation System Chapter 10 Emission of Herbal Woods to Deal with Pollution and Diseases: Pandemic-Based Threats Chapter 11 Artificial Neural Networks: A Comprehensive Review Chapter 12 A Case Study on Machine Learning to Predict the Students' Result in Higher Education Chapter 13 Data Analytic Approach for Assessment Status of Awareness of Tuberculosis in Nigeria Chapter 14 Active Learning from an Imbalanced Dataset: A Study Conducted on the Depression, Anxiety, and Stress Dataset Chapter 15 Classification of the Magnetic Resonance Imaging of the Brain Tumor Using the Residual Neural Network Framework
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Data Set;Quantum Machine Learning;Random Forest;Cyber Security and Intrusion Detection;SVM;Fault Detection and Prevention;Health Informatics;Quality Assessment;Elm Classifier;Facial Recognition;Single Layer Feed Forward Neural Network;Computer Vision;KNN Classification;DEA Model;EMG Signal;Arm CPU;Smite;Feature Subset;Student Dataset;Raspberry Pi;Imbalanced Data;Sentiment Score;Received Code Word;Random Forest Classifier;DEA;PSO Algorithm;CNN Architecture;Hidden Neurons;CDF;Message Word;Mango Wood
Chapter 1 Random Variables in Machine Learning Chapter 2 Analysis of EMG Signals using Extreme Learning Machine with Nature Inspired Feature Selection Techniques Chapter 3 Detection of Breast Cancer by Using Various Machine Learning and Deep Learning Algorithms Chapter 4 Assessing the Radial Efficiency Performance of Bus Transport Sector Using Data Envelopment Analysis Chapter 5 Weight-Based Codes-A Binary Error Control Coding Scheme-A Machine Learning Approach Chapter 6 Massive Data Classification of Brain Tumors Using DNN: Opportunity in Medical Healthcare 4.0 through Sensors Chapter 7 Deep Learning Approach for Traffic Sign Recognition on Embedded Systems Chapter 8 Lung Cancer Risk Stratification Using ML and AI on Sensor- Based IoT: An Increasing Technological Trend for Health of Humanity Chapter 9 Statistical Feedback Evaluation System Chapter 10 Emission of Herbal Woods to Deal with Pollution and Diseases: Pandemic-Based Threats Chapter 11 Artificial Neural Networks: A Comprehensive Review Chapter 12 A Case Study on Machine Learning to Predict the Students' Result in Higher Education Chapter 13 Data Analytic Approach for Assessment Status of Awareness of Tuberculosis in Nigeria Chapter 14 Active Learning from an Imbalanced Dataset: A Study Conducted on the Depression, Anxiety, and Stress Dataset Chapter 15 Classification of the Magnetic Resonance Imaging of the Brain Tumor Using the Residual Neural Network Framework
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Data Set;Quantum Machine Learning;Random Forest;Cyber Security and Intrusion Detection;SVM;Fault Detection and Prevention;Health Informatics;Quality Assessment;Elm Classifier;Facial Recognition;Single Layer Feed Forward Neural Network;Computer Vision;KNN Classification;DEA Model;EMG Signal;Arm CPU;Smite;Feature Subset;Student Dataset;Raspberry Pi;Imbalanced Data;Sentiment Score;Received Code Word;Random Forest Classifier;DEA;PSO Algorithm;CNN Architecture;Hidden Neurons;CDF;Message Word;Mango Wood
