Pinned Repositories
cd-diagram
Critical difference diagram with Wilcoxon-Holm post-hoc analysis.
cv
EINDM
Fake-Review-Detection
Exploiting Behavioral Features to Detect Fake Reviews by Means of Contextual Features
health_data_science_research_2023
Course website for Summer 2023 offering of CSCI6410/CSCI4148/EPAH6410 Applied Research in Health Data Science at Dalhousie University
HUSMCF
The implementation code of "A Hybrid User Similarity Model for Collaborative Filtering" published in Information Sciences, 2017.
moa
MOA is an open source framework for Big Data stream mining. It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation.
OSDM
This code belongs to ACL conference paper entitled as "An Online Semantic-enhanced Dirichlet Model for Short Text Stream Clustering"
OSGM
This code belongs to paper entitled "An Online Semantic-enhanced Graphical Model for Evolving Short Text Stream Clustering"
OSMTS
This is the code for "Online Semi-supervised Classification on Multi-label Evolving High-Dimensional Text Streams"
JayKumarr's Repositories
JayKumarr/OSDM
This code belongs to ACL conference paper entitled as "An Online Semantic-enhanced Dirichlet Model for Short Text Stream Clustering"
JayKumarr/Fake-Review-Detection
Exploiting Behavioral Features to Detect Fake Reviews by Means of Contextual Features
JayKumarr/HUSMCF
The implementation code of "A Hybrid User Similarity Model for Collaborative Filtering" published in Information Sciences, 2017.
JayKumarr/EINDM
JayKumarr/OSGM
This code belongs to paper entitled "An Online Semantic-enhanced Graphical Model for Evolving Short Text Stream Clustering"
JayKumarr/cd-diagram
Critical difference diagram with Wilcoxon-Holm post-hoc analysis.
JayKumarr/cv
JayKumarr/health_data_science_research_2023
Course website for Summer 2023 offering of CSCI6410/CSCI4148/EPAH6410 Applied Research in Health Data Science at Dalhousie University
JayKumarr/moa
MOA is an open source framework for Big Data stream mining. It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation.
JayKumarr/OSMTS
This is the code for "Online Semi-supervised Classification on Multi-label Evolving High-Dimensional Text Streams"
JayKumarr/Seq2Seq-PyTorch
Sequence to Sequence Models with PyTorch
JayKumarr/Sequence-to-Sequence-Pytorch
This repository contains the sample code of Sequence to Sequence and Regression modeling with LSTM on Pytorch (torch)
JayKumarr/Sports2
JayKumarr/ScMS
JayKumarr/Soft-DTW-TF-Keras
Soft-DTW loss function for keras Tensforflow
JayKumarr/Transfomer_AIS_Pred
JayKumarr/UOSAdmissionSystem