Published 2020-11-03
Keywords
- supervised learning, co-linearity, exceptions/outliers, hyper parameters
How to Cite
A., D. K., Josephine, P. K., V. S., P., & K. S., D. (2020). Supervised Learning Algorithms: A Comparison. Kristu Jayanti Journal of Computational Sciences (KJCS), 1(1), 01–12. https://doi.org/10.59176/kjcs.v1i1.1259
Abstract
Artificial Intelligence is logical systems where the PCs figures out how to take care of an issue, without unequivocally program them. Machine learning is a subset of AI where machines learn based on the data fed to them. A relative report over various AI managed procedures like Linear Regression, K nearest neighbours, Logistic Regression, Decision Trees, Random Forest, Support Vector Machine and Naive Bayes are made in this paper. The correlation depends on assumptions, influences of co-linearity and exceptions, hyper-parameters, shared examination.
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