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Allstate_Claims_Severity

Allstate_Claims_Severity

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When you've been devastated by a serious car accident, your focus is on the things that matter the most: family, friends, and other loved ones. Pushing paper with your insurance agent is the last place you want your time or mental energy spent. This is why Allstate, a personal insurer in the United States, is continually seeking fresh ideas to improve their claims service for the over 16 million households they protect. Allstate is currently developing automated methods of predicting the cost, and hence severity, of claims. In this recruitment challenge, Kagglers are invited to show off their creativity and flex their technical chops by creating an algorithm which accurately predicts claims severity. Aspiring competitors will demonstrate insight into better ways to predict claims severity for the chance to be part of Allstate's efforts to ensure a worry-free customer experience. Each row in this dataset represents an insurance claim. You must predict the value for the 'loss' column. Variables prefaced with 'cat' are categorical, while those prefaced with 'cont' are continuous.

131 features

loss (target)numeric158223 unique values
0 missing
id (row identifier)numeric188318 unique values
0 missing
cat1nominal2 unique values
0 missing
cat2nominal2 unique values
0 missing
cat3nominal2 unique values
0 missing
cat4nominal2 unique values
0 missing
cat5nominal2 unique values
0 missing
cat6nominal2 unique values
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cat7nominal2 unique values
0 missing
cat8nominal2 unique values
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cat9nominal2 unique values
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cat10nominal2 unique values
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cat11nominal2 unique values
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cat12nominal2 unique values
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cat13nominal2 unique values
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cat14nominal2 unique values
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cat15nominal2 unique values
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cat16nominal2 unique values
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cat17nominal2 unique values
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cat18nominal2 unique values
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cat19nominal2 unique values
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cat20nominal2 unique values
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cat21nominal2 unique values
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cat22nominal2 unique values
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cat23nominal2 unique values
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cat24nominal2 unique values
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cat25nominal2 unique values
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cat26nominal2 unique values
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cat27nominal2 unique values
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cat28nominal2 unique values
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cat29nominal2 unique values
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cat30nominal2 unique values
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cat31nominal2 unique values
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cat32nominal2 unique values
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cat33nominal2 unique values
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cat34nominal2 unique values
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cat35nominal2 unique values
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cat36nominal2 unique values
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cat37nominal2 unique values
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cat38nominal2 unique values
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cat39nominal2 unique values
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cat40nominal2 unique values
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cat41nominal2 unique values
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cat42nominal2 unique values
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cat43nominal2 unique values
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cat44nominal2 unique values
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cat45nominal2 unique values
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cat46nominal2 unique values
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cat47nominal2 unique values
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cat48nominal2 unique values
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cat49nominal2 unique values
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cat50nominal2 unique values
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cat51nominal2 unique values
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cat52nominal2 unique values
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cat53nominal2 unique values
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cat54nominal2 unique values
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cat55nominal2 unique values
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cat56nominal2 unique values
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cat57nominal2 unique values
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cat58nominal2 unique values
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cat59nominal2 unique values
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cat60nominal2 unique values
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cat61nominal2 unique values
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cat62nominal2 unique values
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cat63nominal2 unique values
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cat64nominal2 unique values
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cat65nominal2 unique values
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cat66nominal2 unique values
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cat67nominal2 unique values
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cat68nominal2 unique values
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cat69nominal2 unique values
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cat70nominal2 unique values
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cat71nominal2 unique values
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cat72nominal2 unique values
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cat73nominal3 unique values
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cat74nominal3 unique values
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cat75nominal3 unique values
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cat76nominal3 unique values
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cat77nominal4 unique values
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cat78nominal4 unique values
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cat79nominal4 unique values
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cat80nominal4 unique values
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cat81nominal4 unique values
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cat82nominal4 unique values
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cat83nominal4 unique values
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cat84nominal4 unique values
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cat85nominal4 unique values
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cat86nominal4 unique values
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cat87nominal4 unique values
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cat88nominal4 unique values
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cat89nominal8 unique values
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cat90nominal7 unique values
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cat91nominal8 unique values
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cat92nominal7 unique values
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cat93nominal5 unique values
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cat94nominal7 unique values
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cat95nominal5 unique values
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cat96nominal8 unique values
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cat97nominal7 unique values
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cat98nominal5 unique values
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cat99nominal16 unique values
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cat100nominal15 unique values
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cat101nominal19 unique values
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cat102nominal9 unique values
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cat103nominal13 unique values
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cat104nominal17 unique values
0 missing
cat105nominal20 unique values
0 missing
cat106nominal17 unique values
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cat107nominal20 unique values
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cat108nominal11 unique values
0 missing
cat109nominal84 unique values
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cat110nominal131 unique values
0 missing
cat111nominal16 unique values
0 missing
cat112nominal51 unique values
0 missing
cat113nominal61 unique values
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cat114nominal19 unique values
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cat115nominal23 unique values
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cat116nominal326 unique values
0 missing
cont1numeric647 unique values
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cont2numeric33 unique values
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cont3numeric76 unique values
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cont4numeric112 unique values
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cont5numeric141 unique values
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cont6numeric2573 unique values
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cont7numeric5632 unique values
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cont8numeric201 unique values
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cont9numeric347 unique values
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cont10numeric174 unique values
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cont11numeric326 unique values
0 missing
cont12numeric328 unique values
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cont13numeric353 unique values
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cont14numeric18740 unique values
0 missing
Show first 100 features

19 properties

NumberOfInstances
188318
Number of instances (rows) of the dataset.
NumberOfFeatures
131
Number of attributes (columns) of the dataset.
NumberOfClasses
0
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
15
Number of numeric attributes.
NumberOfSymbolicFeatures
116
Number of nominal attributes.
PercentageOfSymbolicFeatures
88.55
Percentage of nominal attributes.
AutoCorrelation
-2670.91
Average class difference between consecutive instances.
PercentageOfNumericFeatures
11.45
Percentage of numeric attributes.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfBinaryFeatures
54.96
Percentage of binary attributes.
NumberOfBinaryFeatures
72
Number of binary attributes.
MinorityClassSize
Number of instances belonging to the least frequent class.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
MajorityClassSize
Number of instances belonging to the most frequent class.
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
Dimensionality
0
Number of attributes divided by the number of instances.
Show all 19 properties

8 tasks

Supervised Regression on Allstate_Claims_Severity
3 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: root_mean_squared_error - target_feature: loss
Supervised Regression on Allstate_Claims_Severity
0 runs - estimation_procedure: 33% Holdout set - target_feature: loss
Clustering on Allstate_Claims_Severity
0 runs - estimation_procedure: 50 times Clustering
Clustering on Allstate_Claims_Severity
0 runs - estimation_procedure: 50 times Clustering
Clustering on Allstate_Claims_Severity
0 runs - estimation_procedure: 50 times Clustering
Clustering on Allstate_Claims_Severity
0 runs - estimation_procedure: 50 times Clustering
Clustering on Allstate_Claims_Severity
0 runs - estimation_procedure: 50 times Clustering
Clustering on Allstate_Claims_Severity
0 runs - estimation_procedure: 50 times Clustering
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