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GitHub / hardikasnani / diamond-price-and-carat-prediction

I leveraged an algorithmic approach to predict the price and carat of the diamond using Machine Learning. Various regression models have been trained and their performance has been evaluated using the R Squared Score followed by tuning of the hyperparameters of top models. I have also carried out a trade-off based on the R Squared Score and the Run-Time to take a situational decision to select the best model.

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hardikasnani%2Fdiamond-price-and-carat-prediction
PURL: pkg:github/hardikasnani/diamond-price-and-carat-prediction

Stars: 1
Forks: 2
Open issues: 0

License: mit
Language: Jupyter Notebook
Size: 694 KB
Dependencies parsed at: Pending

Created at: about 3 years ago
Updated at: over 2 years ago
Pushed at: about 3 years ago
Last synced at: about 2 years ago

Topics: cross-validation-grid-search, diamonds-carat-prediction, diamonds-dataset, diamonds-price-prediction, hyperparamter-tuning, lasso-regression, machine-learning, multivariate-regression, r-squared, random-forest-regression, ridge-regression, run-time, trade-off

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