Implementation of ensemble machine learning algorithms on exome datasets for predicting early diagnosis of cancers.

ABSTRACT: Classification of different cancer types is an essential step in designing a decision support model for early cancer predictions. Using various machine learning (ML) techniques with ensemble learning is one such method used for classifications. In the present study, various ML algorithms were explored on twenty exome datasets, belonging to 5 cancer types. Initially, a data clean-up was carried out on 4181 variants of cancer with 88 features, and a derivative dataset was obtained using natural language processing and probabilistic distribution. An exploratory dataset analysis using principal component analysis was then performed in 1 and 2D axes to reduce the high-dimensionality of the data. To significantly reduce the imbalance in the derivative dataset, oversampling was carried out using

SUBMITTER: Pasha Syed AR 

PROVIDER: S-EPMC9675216 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature