ItemConference Paper

A Dimensionality Reduction Model: A Retrospective Approach on Dementia Triggering Parameters and Feature Ranking

Title
A Dimensionality Reduction Model: A Retrospective Approach on Dementia Triggering Parameters and Feature Ranking
Creator
Maju, Sonam V.; Prakasi, O. S. Gnana
Description
The medical sector has advanced in an imposing way, and are coming up with lifesaving models and wearable devices for disease predictions and patient monitoring. The prediction models and wearable devices will lead to immense amount of data collection leading to the dimensionality issues, overfitting and inaccurate results. From the pool of data that we use for our prediction model, we should be able to identify the required information and parameters which gives a positive contribution to the decision making model. Every dataset with higher number of parameters and high dimensionality will tend to the problems of overfitting. Here, we have a dataset of demented and non-demented patients with five conventional features and other physical parameters. Along with these parameters, we are adding three new prediction parameters like glyhb, BMI and Cholesterol, for proving the association of Diabetics and Dementia. After the addition of these parameters, the dataset will have thirty parameters, and dimensionality reduction is done to avoid the condition of overfitting. The work uses Principal Component Analysis(PCA)for reducing the dimensionality, t-SNE for visualization and K means clustering is used to cluster the target variable. The cluster mean of each variable is used to understand the performance of each variable in each cluster. Later, a basic feature ranking method is also implemented which can be further used for the prediction model. The performance metric used in this research work is Silhouette score, Inertia and Inter-Cluster Distance map. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
Source
Communications in Computer and Information Science;Volume;1951 CCIS;pp.122-134
Date
01-01-2025
Publisher
Springer Science and Business Media Deutschland GmbH
Subject
Clustering; K-means; Principal Component Analysis; Silhouette score; T-Distributed Stochastic Neighbor Embedding(t-SNE)
Coverage
Maju S.V., Christ (Deemed to Be University), Computer Science and Engineering, Kengeri Campus, Mysore Road, Kumbalgodu, kanmanike, Karnataka, Bangalore, 560074, India; Prakasi O.S.G., Christ (Deemed to Be University), Computer Science and Engineering, Kengeri Campus, Mysore Road, Kumbalgodu, kanmanike, Karnataka, Bangalore, 560074, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISSN: 18650929; ISBN: 978-303131722-4;
Format
online
Language
English
Type
Conference paper

Citation

Maju, Sonam V.; Prakasi, O. S. Gnana, “A Dimensionality Reduction Model: A Retrospective Approach on Dementia Triggering Parameters and Feature Ranking,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 20, 2026, https://archives.christuniversity.in/items/show/25302.

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