GitHub - agciss/Machine-Learning-Regression-for-Combined-Cycle-Power-Plant-Data-Set: Training the linear, multiple, polynomial, support vector, decision tree, and random forest regression models. Evaluating of All Model Performance (r-square)

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Training the linear, multiple, polynomial, support vector, decision tree, and random forest regression models. Evaluating of All Model Performance (r-square)

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Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
Decision Tree Regression.ipynb		Decision Tree Regression.ipynb
Random Forest Regression.ipynb		Random Forest Regression.ipynb
Template Support Vector Regression - Agnes Cicilia S. Simanjorang.ipynb		Template Support Vector Regression - Agnes Cicilia S. Simanjorang.ipynb
Template Decision Tree Regression - Agnes Cicilia S. Simanjorang.ipynb		Template Decision Tree Regression - Agnes Cicilia S. Simanjorang.ipynb
Template Multiple Linear Regression.ipynb		Template Multiple Linear Regression.ipynb
Template Polynomial Linear Regression.ipynb		Template Polynomial Linear Regression.ipynb
Template Random Forest Regression - Agnes Cicilia S. Simanjorang.ipynb		Template Random Forest Regression - Agnes Cicilia S. Simanjorang.ipynb
Template Support Vector Regression - Agnes Cicilia S. Simanjorang.ipynb		Template Support Vector Regression - Agnes Cicilia S. Simanjorang.ipynb
Template Support Vector Regression.ipynb		Template Support Vector Regression.ipynb

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Training the linear, multiple, polynomial, support vector, decision tree, and random forest regression models. Evaluating of All Model Performance (r-square)