Binary Classification for High Dimensional Data using Supervised Non-Parametric Ensemble Method
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Abstract (arXiv)
High dimensional data for classification does create many difficulties for machine learning algorithms. The generalization can be done using ensemble learning methods such as bagging based supervised non-parametric random forest algorithm. In this paper we solve the problem of binary classification for high dimensional data using random forest for polycystic ovary syndrome dataset. We have performed the implementation and provided a detailed visualization of the data for general inference. The training accuracy that we have achieved is 95.6% and validation accuracy over 91.74% respectively.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 5 of its 41 references that are in the map. First posted on arXiv 15 Feb 2022.
Builds on
5 of 41 references.
References · 5
- 2020Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlationcited by 420
- 2016Generalized Random Forestscited by 309
- 2017A Tutorial on Kernel Density Estimation and Recent Advancescited by 100
- 2022Succinct Differentiation of Disparate Boosting Ensemble Learning Methods for Prognostication of Polycystic Ovary Syndrome Diagnosiscited by 9
- 2022Discriminant Analysis in Contrasting Dimensions for Polycystic Ovary Syndrome Prognosticationcited by 9
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Citing papers per year: 2022: 6; 2023: 1; 2024: 0; 2025: 1.
8 papers.
- 2022Combining Varied Learners for Binary Classification using Stacked Generalizationcited by 4
- 2022Detection of Tool based Edited Images from Error Level Analysis and Convolutional Neural Networkcited by 2
- 2022Residual-Concatenate Neural Network with Deep Regularization Layers for Binary Classificationcited by 2
- 2022Forged Image Detection using SOTA Image Classification Deep Learning Methods for Image Forensics with Error Level Analysiscited by 1
- 2022Performance Comparison of Simple Transformer and Res-CNN-BiLSTM for Cyberbullying Classificationcited by 0
- 2022Metric Effects based on Fluctuations in values of k in Nearest Neighbor Regressorcited by 0
- 2023Deep Linear Discriminant Analysis with Variation for Polycystic Ovary Syndrome Classificationcited by 0
- 2025A Multi-Component Reward Function with Policy Gradient for Automated Feature Selection with Dynamic Regularization and Bias Mitigationcited by 0
- 2025A Multi-Component Reward Function with Policy Gradient for Automated Feature Selection with Dynamic Regularization and Bias Mitigation9 Oct 2025
- 2023Deep Linear Discriminant Analysis with Variation for Polycystic Ovary Syndrome Classification25 Mar 2023
- 2022Forged Image Detection using SOTA Image Classification Deep Learning Methods for Image Forensics with Error Level Analysis28 Nov 2022
- 2022Metric Effects based on Fluctuations in values of k in Nearest Neighbor Regressor24 Aug 2022
- 2022Performance Comparison of Simple Transformer and Res-CNN-BiLSTM for Cyberbullying Classification5 Jun 2022
- 2022Residual-Concatenate Neural Network with Deep Regularization Layers for Binary Classification25 May 2022
- 2022Detection of Tool based Edited Images from Error Level Analysis and Convolutional Neural Network19 Apr 2022
- 2022Combining Varied Learners for Binary Classification using Stacked Generalization17 Feb 2022