Stratified sampling for feature subspace selection in random forests for high dimensional data
For high dimensional data a large portion of features are often not informative of the class of
the objects. Random forest algorithms tend to use a simple random sampling of features in …
the objects. Random forest algorithms tend to use a simple random sampling of features in …
Recent advances in scaling‐down sampling methods in machine learning
Data sampling methods have been investigated for decades in the context of machine
learning and statistical algorithms, with significant progress made in the past few years …
learning and statistical algorithms, with significant progress made in the past few years …
Stratified feature sampling method for ensemble clustering of high dimensional data
L **g, K Tian, JZ Huang - Pattern Recognition, 2015 - Elsevier
High dimensional data with thousands of features present a big challenge to current
clustering algorithms. Sparsity, noise and correlation of features are common characteristics …
clustering algorithms. Sparsity, noise and correlation of features are common characteristics …
[PDF][PDF] Machine learning based approach to financial fraud detection process in mobile payment system
Mobile payment fraud is the unauthorized use of mobile transaction through identity theft or
credit card stealing to fraudulently obtain money. Mobile payment fraud is the fast growing …
credit card stealing to fraudulently obtain money. Mobile payment fraud is the fast growing …
The mediating role of communication skills in the relationship between leadership style and 21st-century skills
S Demirdag - South African Journal of Education, 2022 - journals.co.za
With the study reported on here I aimed to examine the mediating role of communication
skills in the relationship between leadership styles and 21st-century skills. A correlational …
skills in the relationship between leadership styles and 21st-century skills. A correlational …
Discovering the skyline of web databases
Many web databases are" hidden" behind proprietary search interfaces that enforce the top-
$ k $ output constraint, ie, each query returns at most $ k $ of all matching tuples …
$ k $ output constraint, ie, each query returns at most $ k $ of all matching tuples …
Query reranking as a service
The ranked retrieval model has rapidly become the de facto way for search query
processing in client-server databases, especially those on the web. Despite of the extensive …
processing in client-server databases, especially those on the web. Despite of the extensive …
Aggregate estimation over dynamic hidden web databases
Many databases on the web are" hidden" behind (ie, accessible only through) their
restrictive, form-like, search interfaces. Recent studies have shown that it is possible to …
restrictive, form-like, search interfaces. Recent studies have shown that it is possible to …
Euclidean distance stratified random sampling based clustering model for big data mining
Big data mining is related to large‐scale data analysis and faces computational cost‐related
challenges due to the exponential growth of digital technologies. Classical data mining …
challenges due to the exponential growth of digital technologies. Classical data mining …
Evaluating federated search tools: usability and retrievability framework
Purpose–This study aims to explore a framework for evaluating and comparing two
federated search tools (FSTs) using two different retrieval protocols: XML gateways and Z39 …
federated search tools (FSTs) using two different retrieval protocols: XML gateways and Z39 …