Google earth engine cloud computing platform for remote sensing big data applications: A comprehensive review
M Amani, A Ghorbanian, SA Ahmadi… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
Remote sensing (RS) systems have been collecting massive volumes of datasets for
decades, managing and analyzing of which are not practical using common software …
decades, managing and analyzing of which are not practical using common software …
Automatic construction of decision trees from data: A multi-disciplinary survey
SK Murthy - Data mining and knowledge discovery, 1998 - Springer
Decision trees have proved to be valuable tools for the description, classification and
generalization of data. Work on constructing decision trees from data exists in multiple …
generalization of data. Work on constructing decision trees from data exists in multiple …
Heart disease identification method using machine learning classification in e-healthcare
Heart disease is one of the complex diseases and globally many people suffered from this
disease. On time and efficient identification of heart disease plays a key role in healthcare …
disease. On time and efficient identification of heart disease plays a key role in healthcare …
Multi-stage optimized machine learning framework for network intrusion detection
Cyber-security garnered significant attention due to the increased dependency of individuals
and organizations on the Internet and their concern about the security and privacy of their …
and organizations on the Internet and their concern about the security and privacy of their …
[HTML][HTML] Analysis of diabetes mellitus for early prediction using optimal features selection
Diabetes is a chronic disease or group of metabolic disease where a person suffers from an
extended level of blood glucose in the body, which is either the insulin production is …
extended level of blood glucose in the body, which is either the insulin production is …
[图书][B] An introduction to machine learning
M Kubat - 2017 - Springer
Machine learning has come of age. And just in case you might think this is a mere platitude,
let me clarify. The dream that machines would one day be able to learn is as old as …
let me clarify. The dream that machines would one day be able to learn is as old as …
A survey of clustering algorithms for big data: Taxonomy and empirical analysis
Clustering algorithms have emerged as an alternative powerful meta-learning tool to
accurately analyze the massive volume of data generated by modern applications. In …
accurately analyze the massive volume of data generated by modern applications. In …
Survey of state-of-the-art mixed data clustering algorithms
Mixed data comprises both numeric and categorical features, and mixed datasets occur
frequently in many domains, such as health, finance, and marketing. Clustering is often …
frequently in many domains, such as health, finance, and marketing. Clustering is often …
Evaluation of clustering algorithms for financial risk analysis using MCDM methods
The evaluation of clustering algorithms is intrinsically difficult because of the lack of objective
measures. Since the evaluation of clustering algorithms normally involves multiple criteria, it …
measures. Since the evaluation of clustering algorithms normally involves multiple criteria, it …