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

  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.

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.