Popular repositories Loading

1. n-est-tuning-effects-kushan-sandunil n-est-tuning-effects-kushan-sandunil Public

   This code was design as a part of a research where effects of "n_estimators" of random forest regression was investigated when predicting porosity.

   Jupyter Notebook

2. effects-of-tuning-decision-trees-in-random-forest-regression-on-predicting-porosity-kushan-sandunil- effects-of-tuning-decision-trees-in-random-forest-regression-on-predicting-porosity-kushan-sandunil- Public

   This code was design as a part of a research where effects of "n_estimators" hyperparaemter of random forest regression was investigated when predicting porosity of a hydrocarbon reservoir.

   Jupyter Notebook

3. impact-of-various-train-test-ratios-on-the-performance-of-boosting-ensemble-machine-learning-models impact-of-various-train-test-ratios-on-the-performance-of-boosting-ensemble-machine-learning-models Public

   Codes in this repository was developed as a part of a research done on "Impact of Various Train-Test Ratios on the Performance of Boosting Ensemble Learning Models in Formation Porosity Prediction …

   Jupyter Notebook

4. porosity_prediction_for_CCS_assessment_using_boosting_ensemble_machine-learning_algorithms porosity_prediction_for_CCS_assessment_using_boosting_ensemble_machine-learning_algorithms Public

   This code was developed as a part of a study where feasibility of boosting ensemble machine learning models were investigated in porosity prediction of a carbon capture and storage assessment program

   Jupyter Notebook

5. effects-of-tuning-hyperparameters-in-random-forest-regression-on-reservoir-s-porosity-prediction effects-of-tuning-hyperparameters-in-random-forest-regression-on-reservoir-s-porosity-prediction Public

   These codes were developed as a part of a research where effects of three commonly used hyperparameters of random forest regression, namely, n_estimators, max_features and min_samples_leaf were inv…

   Jupyter Notebook

6. bagging-ensembles-in-porosity-prediction-for-carbon-dioxide-capture-and-storage-assessment-kushan bagging-ensembles-in-porosity-prediction-for-carbon-dioxide-capture-and-storage-assessment-kushan Public

   These codes were developed as a part of a research done on investigating the usability of ensemble algorithms in porosity prediction in carbon capture and storage assessment programs

   Jupyter Notebook