Active Transfer Learning using KNIME

Recently, I read this article
https://medium.com/pytorch/active-transfer-learning-with-pytorch-71ed889f08c1

Active transfer learning looked fun and do-able using KNIME too. SO had a play around with KNIME workflow and got this.

Learns the probability of model being correct or not using transfer learning. Because the output was binary, instead of adding output layer, I just let the last layer retrainable. I hope I'm doing things right... If not, I can modify this easily anyway. I probably ask my colleague someday.

SO I let this run then it did seem to plateau at some point. I was running for 1000 times as the default setting of active learning loop was 1000 but with only 6000 or so datapoints, I didn't need to run that much too. Went to sleep, woke up, and the loop was at 968th time. haha, another experiment anyway.

Running this again and trying to see the best hyperparameters and everything. Another fun for today!!