APPLICATION OF SUPERVISED LEARNING
MACHINE LEARNING PIPELINE
|
Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
|
|
|
Yes, the model performance always increases
|
|
|
No, model performance always decreases
|
|
|
The model performance may increase, but it can lead to overfitting
|
|
|
The model performance may increase, but it can lead to underfitting
|
Detailed explanation-1: -More training data improves AI performance up to a certain point but can compromise performance beyond it. The quality of the data used to train AI is just as important as the quantity. Poor data quality leads to poor AI results.
Detailed explanation-2: -Having more data certainly increases the accuracy of your model, but there comes a stage where even adding infinite amounts of data cannot improve any more accuracy. This is what we called the natural noise of the data.
Detailed explanation-3: -Perhaps the easiest and most straightforward way to improve your model’s performance and increase its accuracy is to add more data samples to the training data. Doing so will add more details to your data and finetune your model resulting in a more accurate performance.