I have this data set for crimes of a 12 month time period , over 250k rows and i want to predict future...












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I have this 250k data set with these features



    date_time       FullAddress             call_type priority   lat       long
0 6/14/17 21:54 10 14TH ST, San Diego, CA 1151 2.0 32.705449 -117.151870
1 3/29/17 22:24 10 14TH ST, San Diego, CA 1016 2.0 32.705449 -117.151870
2 6/3/17 18:04 10 14TH ST, San Diego, CA 1016 2.0 32.705449 -117.151870
3 3/17/17 10:57 10 14TH ST, San Diego, CA 1151 2.0 32.705449 -117.151870
4 3/3/17 23:45 10 15TH ST, San Diego, CA 911P 2.0 32.705722 -117.15035


Date and time , full address , lat and long , and call type , and level of the seriousness of the crime.
I want to predict the time when Future crimes will happen or predict the location it will happen again. How can i make that happen , will i use regression or classification ? i already predicted the priority, but how can i predict the time it will happen or the location ?



I predicted the priority but doesnt really give me anything . I want to predict time and location or either or.



this is some code i have for my priority prediction



from sklearn.ensemble import RandomForestClassifier
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)
my_RandomForest = RandomForestClassifier(n_estimators=100, random_state=0)

my_RandomForest.fit(X_train, y_train)
y_predict_fr = my_RandomForest.predict(X_test)
from sklearn.metrics import accuracy_score
print(y_predict_fr)
accuracy_fr = accuracy_score(y_test, y_predict_fr)
print(accuracy_fr)

[4. 3. 2. ... 3. 1. 2.]
0.95100761598545
```








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    $begingroup$


    I have this 250k data set with these features



        date_time       FullAddress             call_type priority   lat       long
    0 6/14/17 21:54 10 14TH ST, San Diego, CA 1151 2.0 32.705449 -117.151870
    1 3/29/17 22:24 10 14TH ST, San Diego, CA 1016 2.0 32.705449 -117.151870
    2 6/3/17 18:04 10 14TH ST, San Diego, CA 1016 2.0 32.705449 -117.151870
    3 3/17/17 10:57 10 14TH ST, San Diego, CA 1151 2.0 32.705449 -117.151870
    4 3/3/17 23:45 10 15TH ST, San Diego, CA 911P 2.0 32.705722 -117.15035


    Date and time , full address , lat and long , and call type , and level of the seriousness of the crime.
    I want to predict the time when Future crimes will happen or predict the location it will happen again. How can i make that happen , will i use regression or classification ? i already predicted the priority, but how can i predict the time it will happen or the location ?



    I predicted the priority but doesnt really give me anything . I want to predict time and location or either or.



    this is some code i have for my priority prediction



    from sklearn.ensemble import RandomForestClassifier
    X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)
    my_RandomForest = RandomForestClassifier(n_estimators=100, random_state=0)

    my_RandomForest.fit(X_train, y_train)
    y_predict_fr = my_RandomForest.predict(X_test)
    from sklearn.metrics import accuracy_score
    print(y_predict_fr)
    accuracy_fr = accuracy_score(y_test, y_predict_fr)
    print(accuracy_fr)

    [4. 3. 2. ... 3. 1. 2.]
    0.95100761598545
    ```








    share







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    David Arriaga is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.







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      $begingroup$


      I have this 250k data set with these features



          date_time       FullAddress             call_type priority   lat       long
      0 6/14/17 21:54 10 14TH ST, San Diego, CA 1151 2.0 32.705449 -117.151870
      1 3/29/17 22:24 10 14TH ST, San Diego, CA 1016 2.0 32.705449 -117.151870
      2 6/3/17 18:04 10 14TH ST, San Diego, CA 1016 2.0 32.705449 -117.151870
      3 3/17/17 10:57 10 14TH ST, San Diego, CA 1151 2.0 32.705449 -117.151870
      4 3/3/17 23:45 10 15TH ST, San Diego, CA 911P 2.0 32.705722 -117.15035


      Date and time , full address , lat and long , and call type , and level of the seriousness of the crime.
      I want to predict the time when Future crimes will happen or predict the location it will happen again. How can i make that happen , will i use regression or classification ? i already predicted the priority, but how can i predict the time it will happen or the location ?



      I predicted the priority but doesnt really give me anything . I want to predict time and location or either or.



      this is some code i have for my priority prediction



      from sklearn.ensemble import RandomForestClassifier
      X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)
      my_RandomForest = RandomForestClassifier(n_estimators=100, random_state=0)

      my_RandomForest.fit(X_train, y_train)
      y_predict_fr = my_RandomForest.predict(X_test)
      from sklearn.metrics import accuracy_score
      print(y_predict_fr)
      accuracy_fr = accuracy_score(y_test, y_predict_fr)
      print(accuracy_fr)

      [4. 3. 2. ... 3. 1. 2.]
      0.95100761598545
      ```








      share







      New contributor




      David Arriaga is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.







      $endgroup$




      I have this 250k data set with these features



          date_time       FullAddress             call_type priority   lat       long
      0 6/14/17 21:54 10 14TH ST, San Diego, CA 1151 2.0 32.705449 -117.151870
      1 3/29/17 22:24 10 14TH ST, San Diego, CA 1016 2.0 32.705449 -117.151870
      2 6/3/17 18:04 10 14TH ST, San Diego, CA 1016 2.0 32.705449 -117.151870
      3 3/17/17 10:57 10 14TH ST, San Diego, CA 1151 2.0 32.705449 -117.151870
      4 3/3/17 23:45 10 15TH ST, San Diego, CA 911P 2.0 32.705722 -117.15035


      Date and time , full address , lat and long , and call type , and level of the seriousness of the crime.
      I want to predict the time when Future crimes will happen or predict the location it will happen again. How can i make that happen , will i use regression or classification ? i already predicted the priority, but how can i predict the time it will happen or the location ?



      I predicted the priority but doesnt really give me anything . I want to predict time and location or either or.



      this is some code i have for my priority prediction



      from sklearn.ensemble import RandomForestClassifier
      X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)
      my_RandomForest = RandomForestClassifier(n_estimators=100, random_state=0)

      my_RandomForest.fit(X_train, y_train)
      y_predict_fr = my_RandomForest.predict(X_test)
      from sklearn.metrics import accuracy_score
      print(y_predict_fr)
      accuracy_fr = accuracy_score(y_test, y_predict_fr)
      print(accuracy_fr)

      [4. 3. 2. ... 3. 1. 2.]
      0.95100761598545
      ```






      scikit-learn pandas





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      David Arriaga is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.










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      Check out our Code of Conduct.








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      asked 2 mins ago









      David ArriagaDavid Arriaga

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      David Arriaga is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.






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      Check out our Code of Conduct.






















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