@sonali73 wrote:
I am new to machine learning. I am being given a Machine Learning problem to predict the age at which rail will fail.
Data given consists of many different tables. 10 tables give number of failures in particular year in different zones.A table ‘GMT-wise analysis’ gives number of rail failures in duration 2010-2019 according to GMT values. In ‘GMT-wise analysis’ table given below, <100, 100 to 200…, >800 are values of GMT. ‘Railway’ column tells the zone of rail track,
Similarly ‘age-wise analysis’, ‘location-wise analysis’ tables are provided.
Is it possible to determine the age/GMT at which rail will fail given other features of rail, like UTS,zone, location? If yes, pease provide the hint for the same.
I have searched before posting questions but didn’t find anything that can help in solving this problem.
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