I have this data set for crimes of a 12 month time period , over 250k rows and i want to predict future...
$begingroup$
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
```
scikit-learn pandas
asked 9 mins ago
David ArriagaDavid Arriaga
1
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add a comment |
$begingroup$
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
```
scikit-learn pandas
asked 9 mins ago
David ArriagaDavid Arriaga
1
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.
$endgroup$
add a comment |
$begingroup$
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
```
scikit-learn pandas
asked 9 mins ago
David ArriagaDavid Arriaga
1
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
scikit-learn pandas
asked 9 mins ago
David ArriagaDavid Arriaga
1
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.
asked 9 mins ago
David ArriagaDavid Arriaga
1
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.
asked 9 mins ago
David ArriagaDavid Arriaga
1
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.
asked 9 mins ago
David ArriagaDavid Arriaga
1
asked 9 mins ago
David ArriagaDavid Arriaga
1
1
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.
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.
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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