4 Conclusion Four machine learning methods were assessed. k-NN and decision trees had lower accuracy due to skewed string vectors, making them unsuitable. Logistic Regression outperformed, excelling in categorizing floating point values and achieving higher accuracy. However, it struggled to identify associations among vectors. This underscores algorithm selection’s importance in optimizing predictive modelling, especially with intricate feature connections and diverse data distributions.
Contributions
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Proposal Coding Presentation Report
Ridhi Mehra
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Shloka Mohanty Mrugank Pednekar Mitanshu Thakore
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