when a ML Model has high bias, getting more training data will help in improving the model ? true or false
Answers
When a ML Model or Machine Learning has high bias that indicates two things, the first one denotes that the algorithm itself has been coded in such a way that in any scenarios it is not possible to change the rigidity, and the other option is that as the ML algorithm is made in such a way that it may learn with any incidents occurring. So it may also happen that some logic may fail in front of the value of past experience and the algorithm had been designed with that perspective, so if the scenario is type of the second case then the answer to the question is True.
The answer is true.
When we go for the high bias then it will mean that the data is simple.
If one thing are simple then it will be easy to obtain the training set without complicating the whole process.
Also, the high bias works as the under fitting work that shows the proper model as per the ability to function up in a model.