A robust incremental learning method for non-stationary environments

Classification of Students using Psychometric Tests with the help of Incremental Naïve Bayes Algorithm

“…In [13] and [14], the incremental leaning for independent navigation system was proposed. Some additional work on incremental leaning includes, the parameter incremental learning algorithm for Multilayer Perceptron [15], for concept drift detection [16,17], online face recognition [18,19]. Section 2 gives the methodology applied in the work and the description of the algorithm used, while section 3 mentions the dataset used and section 4 talks about the result and finally section 5 concludes the research.…”

Learning from non-stationary data using a growing network of prototypes

“…Other approaches use neural networks [10], dynamic Generalized Linear Models [16], a learning Kalman filter framework [17], or Genetic Programming [18].…”

“…In order to be able to compare our results to published data ( [7], [10]) we also provide the evaluation method used for each dataset. We shall use this same evaluation method in our experiments.…”

“…The New South Wales Electricity Market Pricing dataset (elec2) was first proposed in [30] and is also used in [10], [31]. It contains samples collected at 30-minute intervals that detail demand in New South Wales, Victoria, and amount of electricity scheduled to be exchanged between those Australian states.…”

“…This restrictive definition, however, provides little insight on the key issues of IL. Other more detailed definitions [7]- [10] include a mixture of task features that incremental algorithms need to address. They vary slightly depending on whether the topic of the paper is related to learning from large datasets, or to learning from data streams.…”