APPLICATION OF SUPERVISED LEARNING
SUPERVISED AND UNSUPERVISED LEARNING
|
Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
|
what are the key challenges in successfully training machine learning model?
|
|
Features available in the data sets
|
|
|
Algorithms that are suitable for the task
|
|
|
Hyper parameters Tuning
|
|
|
Evaluation Metrics
|
Explanation:
Detailed explanation-1: -Accuracy, confusion matrix, log-loss, and AUC-ROC are the most popular evaluation metrics used for evaluating classifier performance.
Detailed explanation-2: -Lack of quality training data. Incorrect training data. Poor data quality. Introduction of implicit biases.
There is 1 question to complete.