PROGRESSIVE LEARNING - UNIVERSAL CLASSIFIER
Research Aim
To integrate the progressive learning technique with the universal classifier, thereby achieving human-learning-inspired progressively learning universally generic classifier. The resulting new classifier can be used for binary, multi-class and multi-label classification problems with dynamic introduction of new classes.
Research Challenges
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Identification of classification type
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Estimating the number of target labels corresponding to each input sample
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Identifying each of the associated target labels.
Datasets
Binary: Diabetes, Ionosphere
Multi-class: Balance-scale, Satellite image, Digits
Multi-label: Scene, Yeast, Corel5k, Medical
Dataset specifications are given below:
Proposed Approach
The algorithm, code and datasets will be uploaded soon.
Results
The experimental results will be updated soon.