Lowering the cut-off threshold in a classifier can determine:

Lowering the cut-off threshold in a classifier can determine:

an increase of false alarms (FP) as the price to pay to improve sensitivity and a bottom-left shift on the ROC curve
a decrease of false alarms (FP) as the price to pay to improve sensitivity and a top-right shift on the ROC curve
an increase of false alarms (FP) as the price to pay to improve sensitivity and a top-right shift on the ROC curve
a decrease of false alarms (FP) as the price to pay to improve sensitivity and a bottom-right shift on the ROC curve

 

Need assignment help for this question?

If you need assistance with writing your essay, we are ready to help you!

OUR PROCESS

Order

Payment

Writing

Delivery

Why Choose Us: Cost-efficiency, Plagiarism free, Money Back Guarantee, On-time Delivery, Total Сonfidentiality, 24/7 Support, 100% originality

2. What is true about polynomial regression (i.e. polynomial fit in linear regression)?
It can never be considered linear
Sometimes it is linear
Although predictors are not linear, the relationship between parameters or coefficients is linear

3. In machine learning, building a model means:
making an algorithm progressively adjust some numbers called parameters until optimal values are found
setting some numbers called hyperparameters
making an algorithm minimize a cost function which computes an error
both a and c
answers a,b and c

4. Data science is a discipline that:
employs statistical methods and techniques
includes machine learning to automatically learn regularities in datasets
should always be used in conjunction with domain-related disciplines to better assess models
All of the above

5. In the age of Big Data:
rule-based software applications and relational databases are always the best solutions for classification problems
The traditional programming approach should never be used
algorithms for analytics learning predictive models from data are especially recommended and adopted
None of the above

 

0 replies

Leave a Reply

Want to join the discussion?
Feel free to contribute!

Leave a Reply