8 citations · 40 across the 11 of their papers we have counts for
8 papers · 1 filter
Deep Linear Discriminant Analysis with Variation for Polycystic Ovary Syndrome Classification
Raunak Joshi, Abhishek Gupta, Himanshu Soni +1
The polycystic ovary syndrome diagnosis is a problem that can be leveraged using prognostication based learning procedures. Many implementations of PCOS can be seen with Machine Le…
Metric Effects based on Fluctuations in values of k in Nearest Neighbor Regressor
Abhishek Gupta, Raunak Joshi, Nandan Kanvinde +2
Regression branch of Machine Learning purely focuses on prediction of continuous values. The supervised learning branch has many regression based methods with parametric and non-pa…
Residual-Concatenate Neural Network with Deep Regularization Layers for Binary Classification
Abhishek Gupta, Sruthi Nair, Raunak Joshi +1
Many complex Deep Learning models are used with different variations for various prognostication tasks. The higher learning parameters not necessarily ensure great accuracy. This c…
Combining Varied Learners for Binary Classification using Stacked Generalization
Sruthi Nair, Abhishek Gupta, Raunak Joshi +1
The Machine Learning has various learning algorithms that are better in some or the other aspect when compared with each other but a common error that all algorithms will suffer fr…
Effects of Parametric and Non-Parametric Methods on High Dimensional Sparse Matrix Representations
Sayali Tambe, Raunak Joshi, Abhishek Gupta +2
The semantics are derived from textual data that provide representations for Machine Learning algorithms. These representations are interpretable form of high dimensional sparse ma…
Binary Classification for High Dimensional Data using Supervised Non-Parametric Ensemble Method
Nandan Kanvinde, Abhishek Gupta, Raunak Joshi +1
High dimensional data for classification does create many difficulties for machine learning algorithms. The generalization can be done using ensemble learning methods such as baggi…