Low precision and high recall application - Logical regression

0 votes
I'm trying to understand logistic regression and very confused when to use low precision value and high regression value. Can you please explain this with an example?
Jun 13, 2019 in Python by Kamal

1 answer to this question.

0 votes
In situations where you wish to reduce the number of false negatives, you use low precision and high recall. Let me explain what false negative with an example. Suppose you have a dataset of people affected by a disease. You wish to find out people who are affected by the disease. Anybody who is affected shouldn't be classified as not affected. This is called a false negative.
answered Jun 13, 2019 by Meg

Related Questions In Python

0 votes
1 answer
0 votes
0 answers

what is the logical AND operator in python?

how do i use it in a ...READ MORE

Apr 12, 2019 in Python by Waseem
• 4,540 points
0 votes
1 answer

What does the random.triangular(low, high, mode) function do in python?

It returns a random floating point number ...READ MORE

answered May 27, 2019 in Python by Vinod
0 votes
1 answer

How to pretty-print a numpy.array without scientific notation and with given precision?

Hii @kartik, The numpy arrays have the method round(precision) which ...READ MORE

answered Apr 14 in Python by Niroj
• 68,780 points
+1 vote
2 answers

how can i count the items in a list?

Syntax :            list. count(value) Code: colors = ['red', 'green', ...READ MORE

answered Jul 6, 2019 in Python by Neha
• 330 points

edited Jul 8, 2019 by Kalgi 1,478 views
0 votes
0 answers
0 votes
1 answer

Python logical operator 'and'

If you use and on two or ...READ MORE

answered Jan 28, 2019 in Python by Omkar
• 69,030 points
0 votes
1 answer

Replace First and Last Word of String in the Most Pythonic Way

import re a = " this is a ...READ MORE

answered Aug 22, 2018 in Python by aryya
• 7,380 points