Data
la_crimes

la_crimes

active ARFF Public Domain (CC0) Visibility: public Uploaded 04-10-2019 by Guillaume Lemaitre
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This dataset reflects incidents of crime in the City of Los Angeles dating back to 2010. This data is transcribed from original crime reports that are typed on paper and therefore there may be some inaccuracies within the data. Address fields are only provided to the nearest hundred block in order to maintain privacy. This data is as accurate as the data in the database. Please note questions or concerns in the comments.

26 features

Victim_Age (target)numeric90 unique values
0 missing
DR_Numbernumeric1468825 unique values
0 missing
Date_Reportedstring2830 unique values
0 missing
Date_Occurredstring2830 unique values
0 missing
Time_Occurrednumeric1438 unique values
0 missing
Area_IDnumeric21 unique values
0 missing
Area_Namenominal21 unique values
0 missing
Reporting_Districtnumeric1277 unique values
0 missing
Crime_Codenumeric138 unique values
0 missing
Crime_Code_Descriptionnominal134 unique values
368 missing
MO_Codesstring330050 unique values
149454 missing
Victim_Sexnominal5 unique values
126433 missing
Victim_Descentnominal20 unique values
126458 missing
Premise_Codenumeric298 unique values
36 missing
Premise_Descriptionnominal210 unique values
2756 missing
Weapon_Used_Codenumeric80 unique values
967578 missing
Weapon_Descriptionnominal79 unique values
967579 missing
Status_Codestring8 unique values
1 missing
Status_Descriptionnominal6 unique values
0 missing
Crime_Code_1numeric144 unique values
6 missing
Crime_Code_2numeric134 unique values
1383801 missing
Crime_Code_3numeric52 unique values
1466904 missing
Crime_Code_4numeric11 unique values
1468759 missing
Addressstring70071 unique values
0 missing
Cross_Streetstring10799 unique values
1221634 missing
Location_string60115 unique values
9 missing

62 properties

1468825
Number of instances (rows) of the dataset.
26
Number of attributes (columns) of the dataset.
0
Number of distinct values of the target attribute (if it is nominal).
7881776
Number of missing values in the dataset.
1468811
Number of instances with at least one value missing.
12
Number of numeric attributes.
7
Number of nominal attributes.
Entropy of the target attribute values.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Second quartile (Median) of entropy among attributes.
0
Number of attributes divided by the number of instances.
67.86
Average number of distinct values among the attributes of the nominal type.
-0.73
Second quartile (Median) of kurtosis among attributes of the numeric type.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
-0.97
Mean skewness among attributes of the numeric type.
727.99
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
1871431.2
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
-0.05
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-1.44
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
169.74
Second quartile (Median) of standard deviation of attributes of the numeric type.
21.14
Maximum kurtosis among attributes of the numeric type.
11.13
Minimum of means among attributes of the numeric type.
100
Percentage of instances having missing values.
Third quartile of entropy among attributes.
136616778.98
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
20.64
Percentage of missing values.
7.71
Third quartile of kurtosis among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
5
The minimal number of distinct values among attributes of the nominal type.
46.15
Percentage of numeric attributes.
1112.28
Third quartile of means among attributes of the numeric type.
210
The maximum number of distinct values among attributes of the nominal type.
-4.25
Minimum skewness among attributes of the numeric type.
26.92
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.56
Maximum skewness among attributes of the numeric type.
6.01
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.44
Third quartile of skewness among attributes of the numeric type.
22454838.2
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-1.18
First quartile of kurtosis among attributes of the numeric type.
503.16
Third quartile of standard deviation of attributes of the numeric type.
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
327.17
First quartile of means among attributes of the numeric type.
78.49
Standard deviation of the number of distinct values among attributes of the nominal type.
3.62
Mean kurtosis among attributes of the numeric type.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
11385327.16
Mean of means among attributes of the numeric type.
-2.69
First quartile of skewness among attributes of the numeric type.
-16.94
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
93.42
First quartile of standard deviation of attributes of the numeric type.

8 tasks

0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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