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edited Mar 24, 2021 at 15:51

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I have a dataset is regarding ambulance call data.

Data sample:

     v_type      district   gender  complaint      age  Month
0   Advanced    District 1  Male    Chest Pain      28  jan
1   Advanced    District 2  Male    Heart Problem   50  dec
2   General     District 3  Male    Cardiac Arrest  76  jun
3   Advanced    District 4  Male    Heart Problem   45  oct
4   General     District 5  Female  Cardiac Arrest  52  nov
5   Advanced    District 1  Male    Chest Pain      34  feb
6   Advanced    District 2  Male    Cardiac Arrest  44  jun
7   General     District 3  Female  Heart Problem   55  july
8   Advanced    District 4  Female  Heart Problem   86  may
9   General     District 5  Male    Heart Problem   65  aug
10  General     District 1  Male    Heart Problem   60  nov
11  Advanced    District 2  Male    Chest Pain      36  mar

In the data V_type(Vehicle type)v_type (Vehicle type) we have Advanced(Advanced featured emergency vehicle)Advanced (Advanced featured emergency vehicle) and General(Basic featured emergency vehicle)General (Basic featured emergency vehicle).

Now, howHow to predict that how many advanceadvanced or general ambulances should arrange in a district according tofor a particular month.?

Example: If in a month (jan) and in district3 has huge complaint then predict and need to show 5 or 6.. Advanced vehicle type is required

I have a dataset is regarding ambulance call data.

Data sample:

     v_type      district   gender  complaint      age  Month
0   Advanced    District 1  Male    Chest Pain      28  jan
1   Advanced    District 2  Male    Heart Problem   50  dec
2   General     District 3  Male    Cardiac Arrest  76  jun
3   Advanced    District 4  Male    Heart Problem   45  oct
4   General     District 5  Female  Cardiac Arrest  52  nov
5   Advanced    District 1  Male    Chest Pain      34  feb
6   Advanced    District 2  Male    Cardiac Arrest  44  jun
7   General     District 3  Female  Heart Problem   55  july
8   Advanced    District 4  Female  Heart Problem   86  may
9   General     District 5  Male    Heart Problem   65  aug
10  General     District 1  Male    Heart Problem   60  nov
11  Advanced    District 2  Male    Chest Pain      36  mar

In the data V_type(Vehicle type) we have Advanced(Advanced featured emergency vehicle) and General(Basic featured emergency vehicle)

Now, how to predict that how many advance or general ambulances should arrange in a district according to a particular month.

Example: If in a month (jan) and in district3 has huge complaint then predict and need to show 5 or 6.. Advanced vehicle type is required

I have a dataset is regarding ambulance call data.

Data sample:

     v_type      district   gender  complaint      age  Month
0   Advanced    District 1  Male    Chest Pain      28  jan
1   Advanced    District 2  Male    Heart Problem   50  dec
2   General     District 3  Male    Cardiac Arrest  76  jun
3   Advanced    District 4  Male    Heart Problem   45  oct
4   General     District 5  Female  Cardiac Arrest  52  nov
5   Advanced    District 1  Male    Chest Pain      34  feb
6   Advanced    District 2  Male    Cardiac Arrest  44  jun
7   General     District 3  Female  Heart Problem   55  july
8   Advanced    District 4  Female  Heart Problem   86  may
9   General     District 5  Male    Heart Problem   65  aug
10  General     District 1  Male    Heart Problem   60  nov
11  Advanced    District 2  Male    Chest Pain      36  mar

In the data v_type (Vehicle type) we have Advanced (Advanced featured emergency vehicle) and General (Basic featured emergency vehicle).

How to predict how many advanced or general ambulances should arrange in a district for a particular month?

Example: If in a month (jan) and in district3 has huge complaint then predict and need to show 5 or 6.. Advanced vehicle type is required

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asked Mar 24, 2021 at 13:48

Manoj Kumar

with ML/DL model Is possible predict numbers of items required?

I have a dataset is regarding ambulance call data.

Data sample:

     v_type      district   gender  complaint      age  Month
0   Advanced    District 1  Male    Chest Pain      28  jan
1   Advanced    District 2  Male    Heart Problem   50  dec
2   General     District 3  Male    Cardiac Arrest  76  jun
3   Advanced    District 4  Male    Heart Problem   45  oct
4   General     District 5  Female  Cardiac Arrest  52  nov
5   Advanced    District 1  Male    Chest Pain      34  feb
6   Advanced    District 2  Male    Cardiac Arrest  44  jun
7   General     District 3  Female  Heart Problem   55  july
8   Advanced    District 4  Female  Heart Problem   86  may
9   General     District 5  Male    Heart Problem   65  aug
10  General     District 1  Male    Heart Problem   60  nov
11  Advanced    District 2  Male    Chest Pain      36  mar

In the data V_type(Vehicle type) we have Advanced(Advanced featured emergency vehicle) and General(Basic featured emergency vehicle)

Now, how to predict that how many advance or general ambulances should arrange in a district according to a particular month.

Example: If in a month (jan) and in district3 has huge complaint then predict and need to show 5 or 6.. Advanced vehicle type is required