8 citations · 29 across the 9 of their papers we have counts for
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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…
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…
Discriminant Analysis in Contrasting Dimensions for Polycystic Ovary Syndrome Prognostication
Abhishek Gupta, Himanshu Soni, Raunak Joshi +1
A lot of prognostication methodologies have been formulated for early detection of Polycystic Ovary Syndrome also known as PCOS using Machine Learning. PCOS is a binary classificat…