mlsanityData to 7 Oct 2026

Discriminant Analysis in Contrasting Dimensions for Polycystic Ovary Syndrome Prognostication

arXiv 2201.03029 ↗First posted 9 Jan 2022cs.LGcited by 9

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Abstract (arXiv)

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 classification problem. Dimensionality Reduction methods impact the performance of Machine Learning to a greater extent and using a Supervised Dimensionality Reduction method can give us a new edge to tackle this problem. In this paper we present Discriminant Analysis in different dimensions with Linear and Quadratic form for binary classification along with metrics. We were able to achieve good accuracy and less variation with Discriminant Analysis as compared to many commonly used classification algorithms with training accuracy reaching 97.37% and testing accuracy of 95.92% using Quadratic Discriminant Analysis. Paper also gives the analysis of data with visualizations for deeper understanding of problem.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 3 of its 20 references that are in the map. First posted on arXiv 9 Jan 2022.

Builds on

3 of 20 references.

References · 3

  1. 2018A Tutorial on Bayesian Optimizationcited by 734
  2. 2019Linear and Quadratic Discriminant Analysis: Tutorialcited by 11
  3. 2022Succinct Differentiation of Disparate Boosting Ensemble Learning Methods for Prognostication of Polycystic Ovary Syndrome Diagnosiscited by 9

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Cited by year

Citing papers per year: 2022: 8; 2023: 1.

9 papers.

  1. 2022Binary Classification for High Dimensional Data using Supervised Non-Parametric Ensemble Methodcited by 8
  2. 2022Combining Varied Learners for Binary Classification using Stacked Generalizationcited by 4
  3. 2022Effects of Parametric and Non-Parametric Methods on High Dimensional Sparse Matrix Representationscited by 2
  4. 2022Detection of Tool based Edited Images from Error Level Analysis and Convolutional Neural Networkcited by 2
  5. 2022Residual-Concatenate Neural Network with Deep Regularization Layers for Binary Classificationcited by 2
  6. 2022Prediction of Maneuvering Status for Aerial Vehicles using Supervised Learning Methodscited by 1
  7. 2022Performance Comparison of Simple Transformer and Res-CNN-BiLSTM for Cyberbullying Classificationcited by 0
  8. 2022Metric Effects based on Fluctuations in values of k in Nearest Neighbor Regressorcited by 0
  9. 2023Deep Linear Discriminant Analysis with Variation for Polycystic Ovary Syndrome Classificationcited by 0