Describe a neural network : Neural Network for Multiclass Classifications

The video tutorial covers the use of neural networks for multiclass classification, using the Iris dataset as an example. It explains the process of fitting a model, making predictions, and evaluating accuracy through a confusion matrix. The tutorial then applies these concepts to real-world loan payment data, highlighting the challenges and limitations of neural networks in this context. The video concludes with an evaluation of the model's performance, noting a 60% accuracy in the loan data scenario.

What steps were taken to prepare the loan payment data for classification?

What was the accuracy of the model when predicting the loan status, and what does this indicate?

Discuss the implications of having a Kappa value of 0 in the context of model evaluation.