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Full-Text Articles in Statistical Models
Decision Trees And Their Application For Classification And Regression Problems, Obinna Chilezie Njoku
Decision Trees And Their Application For Classification And Regression Problems, Obinna Chilezie Njoku
MSU Graduate Theses
Tree methods are some of the best and most commonly used methods in the field of statistical learning. They are widely used in classification and regression modeling. This thesis introduces the concept and focuses more on decision trees such as Classification and Regression Trees (CART) used for classification and regression predictive modeling problems. We also introduced some ensemble methods such as bagging, random forest and boosting. These methods were introduced to improve the performance and accuracy of the models constructed by classification and regression tree models. This work also provides an in-depth understanding of how the CART models are constructed, …
Assessment And Correction Of Lidar-Derived Dems In The Coastal Marshes Of Louisiana, William M. Lauve
Assessment And Correction Of Lidar-Derived Dems In The Coastal Marshes Of Louisiana, William M. Lauve
LSU Master's Theses
The onset of airborne light detection and ranging (lidar) has resulted in expansive, precise digital elevation models (DEMs). DEMs are essential for modeling complex systems, such as the coastal land margin of Louisiana. They are used for many applications (e.g. tide, storm surge, and ecological modeling) and by diverse groups (e.g. state and federal agencies, NGOs, and academia). However, in a marsh environment, it is difficult for airborne lidar to produce accurate bare-earth measurements and even accurate elevations are rarely verified by ground truth data. The accuracy of lidar in marshes is limited by the sensor’s resolution …