Question

What are scenarios which have lower low training accuracy as well as low test accuracy termed as?
1. High Bias.
2. Low Bias.
3. Over Fitting.
4. High Variance.

Answer 1

Answer:

May by you have too many features, i think you need to increase your data or decrease your number of features.

2- try to change splitting of your data for training and testing, split the dataset to be 90% training and 10% test data.

3- Use cross

Answer 2

Q) What are scenarios that have lower low training accuracy as well as low test accuracy termed?

1. High Bias.

2. Low Bias.

3. High bias high variance.

4. High Variance.  

Option (3) High bias high variance is refer to lower test and training accuracy.

• Bias is the term associated with the total error that occurs in training data.
• So the high bias is for representing lower accuracy in training data only.
• When the error in training is less the low bias is used to represent.
• Variance can be used to show the error in testing data.
• High variance is used when the accuracy provided by the testing data is very less.
• When the error quantity in both training and test data is high, then high bias high variance is used to represent.

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