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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.

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Research Challenges

  1. Identification of classification type

  2. Estimating the number of target labels corresponding to each input sample

  3. Identifying each of the associated target labels.

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Datasets

Binary: Diabetes, Ionosphere

Multi-class: Balance-scale, Satellite image, Digits

Multi-label: Scene, Yeast, Corel5k, Medical

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Dataset specifications are given below:

Proposed Approach

The algorithm, code and datasets will be uploaded soon.

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Results

The experimental results will be updated soon.

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