A Meta-Ensemble Classifier Approach: Random Rotation Forest
نویسندگان
چکیده
منابع مشابه
Classifier Ensemble Framework: a Diversity Based Approach
Pattern recognition systems are widely used in a host of different fields. Due to some reasons such as lack of knowledge about a method based on which the best classifier is detected for any arbitrary problem, and thanks to significant improvement in accuracy, researchers turn to ensemble methods in almost every task of pattern recognition. Classification as a major task in pattern recognition,...
متن کاملThresholding a Random Forest Classifier
The original Random Forest derives the final result with respect to the number of leaf nodes voted for the corresponding class. Each leaf node is treated equally and the class with the most number of votes wins. Certain leaf nodes in the topology have better classification accuracies and others often lead to a wrong decision. Also the performance of the forest for different classes differs due ...
متن کاملRandom Forest Ensemble Visualization
The Random forest model for machine learning has become a very popular data mining algorithm due to its high predictive accuracy as well as simiplicity in execution. The downside is that the model is difficult to interpret. The model consists of a collection of classification trees. Our proposed visualization aggregates the collection of trees based on the number of feature appearances at node ...
متن کاملImproving the explainability of Random Forest classifier - user centered approach.
Machine Learning (ML) methods are now influencing major decisions about patient care, new medical methods, drug development and their use and importance are rapidly increasing in all areas. However, these ML methods are inherently complex and often difficult to understand and explain resulting in barriers to their adoption and validation. Our work (RFEX) focuses on enhancing Random Forest (RF) ...
متن کاملEfficient Learning of Random Forest Classifier using Disjoint Partitioning Approach
Random Forest is an Ensemble Supervised Machine Learning technique. Research work in the area of Random Forest aims at either improving accuracy or improving performance. In this paper we are presenting our research towards improvement in learning time of Random Forest by proposing a new approach called Disjoint Partitioning. In this approach, we are using disjoint partitions of training datase...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Balkan Journal of Electrical and Computer Engineering
سال: 2019
ISSN: 2147-284X
DOI: 10.17694/bajece.502156