Multi-dimensional classification via selective feature augmentation
In multi-dimensional classification (MDC), the semantics of objects are characterized by
multiple class spaces from different dimensions. Most MDC approaches try to explicitly …
multiple class spaces from different dimensions. Most MDC approaches try to explicitly …
Probability-based label enhancement for multi-dimensional classification
Multi-dimensional classification (MDC) assumes that each instance has multiple
heterogeneous class spaces simultaneously, and each class variable describes the …
heterogeneous class spaces simultaneously, and each class variable describes the …
Multi-dimensional classification via decomposed label encoding
In multi-dimensional classification (MDC), a number of class variables are assumed in the
output space with each of them specifying the class membership wrt one heterogeneous …
output space with each of them specifying the class membership wrt one heterogeneous …
Multi-dimensional classification via sparse label encoding
In multi-dimensional classification (MDC), there are multiple class variables in the output
space with each of them corresponding to one heterogeneous class space. Due to the …
space with each of them corresponding to one heterogeneous class space. Due to the …
Multi-dimensional classification via stacked dependency exploitation
Multi-dimensional classification (MDC) aims to build classification models for multiple
heterogenous class spaces simultaneously, where each class space characterizes the …
heterogenous class spaces simultaneously, where each class space characterizes the …
[HTML][HTML] Multi-dimensional classification: paradigm, algorithms and beyond
Multi-dimensional classification (MDC) aims at learning from objects where each of them is
represented by a single instance while associated with multiple class variables. In recent …
represented by a single instance while associated with multiple class variables. In recent …
Decomposition-based classifier chains for multi-dimensional classification
In multi-dimensional classification, the semantics of objects are characterized by multiple
class variables from different dimensions. To model the dependencies among class …
class variables from different dimensions. To model the dependencies among class …
Maximum margin multi-dimensional classification
Multi-dimensional classification (MDC) assumes heterogeneous class spaces for each
example, where class variables from different class spaces characterize semantics of the …
example, where class variables from different class spaces characterize semantics of the …
MD-KNN: An instance-based approach for multi-dimensional classification
Multi-dimensional classification (MDC) deals with the problem where each instance is
associated with multiple class variables, each of which corresponds to a specific class …
associated with multiple class variables, each of which corresponds to a specific class …
Data-Driven Multi-target Prediction Analysis for Driving Pattern Recognition: A Machine Learning Approach to Enhance Prediction Accuracy
S Pourroostaei Ardakani, A Cheshmehzangi - Big Data Analytics for Smart …, 2023 - Springer
The driving pattern is critical in life quality enhancement, road traffic minimisation, and
transportation risk reduction. It includes several parameters, such as the car's speed, traffic …
transportation risk reduction. It includes several parameters, such as the car's speed, traffic …