Source: Deep Learning on Medium
Task: checking for LBW out
data: x1..pitch in line; x2 : impact; x3 : not missing stumps
the machine will read data in terms of binary if data is all Ones (aggregation of input is higher than the threshold b )output y will come as one(out), if not output as zero(not out).
Here the point is how we have to define the threshold b?
Now we will see the non-boolean example
Task: to convert data to boolean based on the threshold
data: different features of mobile phones
the threshold b we can define by our requirements ex. a launch date or memory etc..
if phone data is greater than the threshold data can be treated as one.
and we can decide is the is liked or not by total aggregation of inputs is greater than the threshold .