Add to ORKG"Class imbalance may reduce the classifier performance in several recognition pattern problems. Such negative effect is more notable with least represented class (minority class) Patterns. A strategy for handling this problem consisted of treating the cl
Imbalance datasets exist in many real-world domains. It is straightforward to apply classification a...
The class imbalance problem in the multi-class dataset is more challenging to manage than the proble...
In text categorization applications, class imbalance, which refers to an uneven data distribution wh...
En diversos problemas de reconocimiento de patrones, se ha observado que el desequilibrio de clases ...
En diversos problemas de reconocimiento de patrones, se ha observado que el desequilibrio de clases ...
In pattern recognition, it is well known that the classifier performance depends on the classificati...
In pattern recognition, it is well known that the classifier performance depends on the classificati...
Most existing classification approaches assume the underlying training set is evenly distributed. In...
In the classification process that contains class imbalance problems. In addition to the uneven dist...
Problems of Class Imbalance in data classification have received attention from many researchers. It...
The present paper studies the influence of two distinct factors on the performance of some resamplin...
Classification of data has become an important research area. The process of classifying documents i...
Research carried out by the scientific community has shown that the performance of the classifiers d...
The imbalanced learning problem (learning from imbalanced data) presents a significant new challenge...
a r t i c l e i n f o ling with s class distributions, the classification problem becomes more diffi...
Imbalance datasets exist in many real-world domains. It is straightforward to apply classification a...
The class imbalance problem in the multi-class dataset is more challenging to manage than the proble...
In text categorization applications, class imbalance, which refers to an uneven data distribution wh...
En diversos problemas de reconocimiento de patrones, se ha observado que el desequilibrio de clases ...
En diversos problemas de reconocimiento de patrones, se ha observado que el desequilibrio de clases ...
In pattern recognition, it is well known that the classifier performance depends on the classificati...
In pattern recognition, it is well known that the classifier performance depends on the classificati...
Most existing classification approaches assume the underlying training set is evenly distributed. In...
In the classification process that contains class imbalance problems. In addition to the uneven dist...
Problems of Class Imbalance in data classification have received attention from many researchers. It...
The present paper studies the influence of two distinct factors on the performance of some resamplin...
Classification of data has become an important research area. The process of classifying documents i...
Research carried out by the scientific community has shown that the performance of the classifiers d...
The imbalanced learning problem (learning from imbalanced data) presents a significant new challenge...
a r t i c l e i n f o ling with s class distributions, the classification problem becomes more diffi...
Imbalance datasets exist in many real-world domains. It is straightforward to apply classification a...
The class imbalance problem in the multi-class dataset is more challenging to manage than the proble...
In text categorization applications, class imbalance, which refers to an uneven data distribution wh...