We have previously described an incremental learning algorithm, Learn++. NC, for learning
from new datasets that may include new concept classes without accessing previously seen …

Multiple classifier systems tend to suffer from outvoting when new concept classes need to
be learned incrementally. Out-voting is primarily due to existing classifiers being unable to …

An ensemble of classifiers based algorithm, Learn++, was recently introduced that is
capable of incrementally learning new information from datasets that consecutively become …

We have previously introduced an incremental learning algorithm Learn++, which learns
novel information from consecutive data sets by generating an ensemble of classifiers with …

We had previously introduced Learn++, inspired in part by the ensemble based AdaBoost
algorithm, for incrementally learning from new data, including new concept classes, without …

An ensemble based algorithm, Learn++. MT2, is introduced as an enhanced alternative to
our previously reported incremental learning algorithm, Learn++. Both algorithms are …

We have recently introduced an incremental learning algorithm, Learn++. NSE, designed to
learn in nonstationary environments, and has been shown to provide an attractive solution to …

One pass learning updates a model with only a single scan of the dataset, without storing
historical data. Previous studies focus on classification tasks with a fixed class set, and will …

Incremental learning is a machine learning paradigm where the learning process takes
place whenever new example/s emerge and adjusts what has been learned according to …

We have recently introduced an incremental learning algorithm, Learn++. NSE, for N on-S
tationary E nvironments, where the data distribution changes over time due to concept drift …