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ML-abalone

In this project, the abalone dataset, that was collected from UC Irvine Machine Learning Repository. A regression and classification problem have been solved with great success.

Regression

A two layer cross validated regularized linear regression and ANN regression were done, where an R^2 score of 0.95 was achieved. With this the viscera weight could be estimated, which is normally a very tedious proces to estimate by conventional means.

Classification

Various different ML-models were constructed to determine the gender of our abalone data based on the features. The accuracy for the models were between 79% and 84%.

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ML-project that tries to classify abalone in genders based on physical features as well as regression

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