Automated Backward and Forward Selection On Python
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Updated
Nov 12, 2020 - Python
Automated Backward and Forward Selection On Python
Implementation of backward elimination algorithm used for dimensionality reduction for improving the performance of risk calculation in life insurance industry.
Domain-Agnostic Supervised Learning with Hyperdimensional Computing
Multiple linear regression has been used in order to provide a predictions regarding the common factors that affect the life expectancy.
Multiple linear regression model implementation with automated backward elimination (with p-value and adjusted r-squared) in Python and R for showing the relationship among profit and types of expenditures and the states.
Classification with Feature Selection and Extraction Methods
Selecting the best startup to invest by analyzing the profit and its expense in different fields using the Multiple Linear Regression
Analyzed financial reports of startups and developed a multiple linear regression model which was optimized using backwards elimination to determine which independent variables were statistically significant to the company's earnings.
Uses nearest neighbor algorithm to find which feature is the best indicator for a certain class attribute
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