Data
SantanderCustomerSatisfaction

SantanderCustomerSatisfaction

active ARFF Publicly available Visibility: public Uploaded 18-05-2020 by Arlind Kadra
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
At Santander our mission is to help people and businesses prosper. We are always looking for ways to help our customers understand their financial health and identify which products and services might help them achieve their monetary goals. Our data science team is continually challenging our machine learning algorithms, working with the global data science community to make sure we can more accurately identify new ways to solve our most common challenge, binary classification problems such as: is a customer satisfied? Will a customer buy this product? Can a customer pay this loan?Dataset taken from Kaggle https://www.kaggle.com/c/santander-customer-transaction-prediction/data

202 features

target (target)nominal2 unique values
0 missing
ID_codenominal200000 unique values
0 missing
var_0numeric94672 unique values
0 missing
var_1numeric108932 unique values
0 missing
var_2numeric86555 unique values
0 missing
var_3numeric74597 unique values
0 missing
var_4numeric63515 unique values
0 missing
var_5numeric141030 unique values
0 missing
var_6numeric38599 unique values
0 missing
var_7numeric103063 unique values
0 missing
var_8numeric98617 unique values
0 missing
var_9numeric49417 unique values
0 missing
var_10numeric128764 unique values
0 missing
var_11numeric130193 unique values
0 missing
var_12numeric9561 unique values
0 missing
var_13numeric115181 unique values
0 missing
var_14numeric79122 unique values
0 missing
var_15numeric19810 unique values
0 missing
var_16numeric86918 unique values
0 missing
var_17numeric137823 unique values
0 missing
var_18numeric139515 unique values
0 missing
var_19numeric144180 unique values
0 missing
var_20numeric127764 unique values
0 missing
var_21numeric140062 unique values
0 missing
var_22numeric90661 unique values
0 missing
var_23numeric24913 unique values
0 missing
var_24numeric105101 unique values
0 missing
var_25numeric14853 unique values
0 missing
var_26numeric127089 unique values
0 missing
var_27numeric60186 unique values
0 missing
var_28numeric35859 unique values
0 missing
var_29numeric88339 unique values
0 missing
var_30numeric145977 unique values
0 missing
var_31numeric77388 unique values
0 missing
var_32numeric85964 unique values
0 missing
var_33numeric112239 unique values
0 missing
var_34numeric25164 unique values
0 missing
var_35numeric122384 unique values
0 missing
var_36numeric96404 unique values
0 missing
var_37numeric79040 unique values
0 missing
var_38numeric115366 unique values
0 missing
var_39numeric112674 unique values
0 missing
var_40numeric141878 unique values
0 missing
var_41numeric131896 unique values
0 missing
var_42numeric31592 unique values
0 missing
var_43numeric15188 unique values
0 missing
var_44numeric127702 unique values
0 missing
var_45numeric169968 unique values
0 missing
var_46numeric93450 unique values
0 missing
var_47numeric154781 unique values
0 missing
var_48numeric152039 unique values
0 missing
var_49numeric140641 unique values
0 missing
var_50numeric32308 unique values
0 missing
var_51numeric143455 unique values
0 missing
var_52numeric121313 unique values
0 missing
var_53numeric33460 unique values
0 missing
var_54numeric144776 unique values
0 missing
var_55numeric128077 unique values
0 missing
var_56numeric103045 unique values
0 missing
var_57numeric35545 unique values
0 missing
var_58numeric113908 unique values
0 missing
var_59numeric37744 unique values
0 missing
var_60numeric113763 unique values
0 missing
var_61numeric159369 unique values
0 missing
var_62numeric74778 unique values
0 missing
var_63numeric97098 unique values
0 missing
var_64numeric59379 unique values
0 missing
var_65numeric108347 unique values
0 missing
var_66numeric47722 unique values
0 missing
var_67numeric137253 unique values
0 missing
var_68numeric451 unique values
0 missing
var_69numeric110346 unique values
0 missing
var_70numeric153193 unique values
0 missing
var_71numeric13527 unique values
0 missing
var_72numeric110115 unique values
0 missing
var_73numeric142582 unique values
0 missing
var_74numeric161058 unique values
0 missing
var_75numeric129383 unique values
0 missing
var_76numeric139317 unique values
0 missing
var_77numeric106809 unique values
0 missing
var_78numeric72254 unique values
0 missing
var_79numeric53212 unique values
0 missing
var_80numeric136432 unique values
0 missing
var_81numeric79065 unique values
0 missing
var_82numeric144829 unique values
0 missing
var_83numeric144281 unique values
0 missing
var_84numeric133766 unique values
0 missing
var_85numeric108437 unique values
0 missing
var_86numeric140594 unique values
0 missing
var_87numeric125296 unique values
0 missing
var_88numeric84918 unique values
0 missing
var_89numeric103522 unique values
0 missing
var_90numeric157210 unique values
0 missing
var_91numeric7962 unique values
0 missing
var_92numeric110743 unique values
0 missing
var_93numeric26708 unique values
0 missing
var_94numeric89146 unique values
0 missing
var_95numeric29388 unique values
0 missing
var_96numeric148099 unique values
0 missing
var_97numeric158739 unique values
0 missing
var_98numeric33266 unique values
0 missing
var_99numeric69301 unique values
0 missing
var_100numeric150727 unique values
0 missing
var_101numeric122295 unique values
0 missing
var_102numeric146237 unique values
0 missing
var_103numeric9376 unique values
0 missing
var_104numeric72627 unique values
0 missing
var_105numeric39115 unique values
0 missing
var_106numeric71065 unique values
0 missing
var_107numeric137827 unique values
0 missing
var_108numeric8525 unique values
0 missing
var_109numeric112172 unique values
0 missing
var_110numeric106121 unique values
0 missing
var_111numeric46464 unique values
0 missing
var_112numeric60482 unique values
0 missing
var_113numeric116496 unique values
0 missing
var_114numeric43084 unique values
0 missing
var_115numeric86729 unique values
0 missing
var_116numeric63467 unique values
0 missing
var_117numeric164469 unique values
0 missing
var_118numeric143667 unique values
0 missing
var_119numeric112403 unique values
0 missing
var_120numeric158269 unique values
0 missing
var_121numeric64695 unique values
0 missing
var_122numeric121768 unique values
0 missing
var_123numeric129893 unique values
0 missing
var_124numeric91022 unique values
0 missing
var_125numeric16059 unique values
0 missing
var_126numeric32411 unique values
0 missing
var_127numeric95711 unique values
0 missing
var_128numeric98200 unique values
0 missing
var_129numeric113425 unique values
0 missing
var_130numeric36638 unique values
0 missing
var_131numeric21465 unique values
0 missing
var_132numeric57923 unique values
0 missing
var_133numeric19236 unique values
0 missing
var_134numeric131620 unique values
0 missing
var_135numeric140774 unique values
0 missing
var_136numeric156615 unique values
0 missing
var_137numeric144397 unique values
0 missing
var_138numeric117429 unique values
0 missing
var_139numeric137294 unique values
0 missing
var_140numeric121384 unique values
0 missing
var_141numeric134444 unique values
0 missing
var_142numeric128613 unique values
0 missing
var_143numeric94372 unique values
0 missing
var_144numeric40595 unique values
0 missing
var_145numeric108526 unique values
0 missing
var_146numeric84314 unique values
0 missing
var_147numeric137559 unique values
0 missing
var_148numeric10608 unique values
0 missing
var_149numeric148504 unique values
0 missing
var_150numeric83660 unique values
0 missing
var_151numeric109667 unique values
0 missing
var_152numeric95823 unique values
0 missing
var_153numeric73728 unique values
0 missing
var_154numeric119342 unique values
0 missing
var_155numeric127457 unique values
0 missing
var_156numeric40634 unique values
0 missing
var_157numeric126534 unique values
0 missing
var_158numeric144556 unique values
0 missing
var_159numeric112830 unique values
0 missing
var_160numeric156274 unique values
0 missing
var_161numeric11071 unique values
0 missing
var_162numeric57396 unique values
0 missing
var_163numeric123168 unique values
0 missing
var_164numeric122744 unique values
0 missing
var_165numeric119403 unique values
0 missing
var_166numeric17902 unique values
0 missing
var_167numeric140955 unique values
0 missing
var_168numeric97227 unique values
0 missing
var_169numeric18242 unique values
0 missing
var_170numeric113721 unique values
0 missing
var_171numeric125914 unique values
0 missing
var_172numeric143366 unique values
0 missing
var_173numeric128120 unique values
0 missing
var_174numeric134945 unique values
0 missing
var_175numeric92659 unique values
0 missing
var_176numeric142521 unique values
0 missing
var_177numeric85720 unique values
0 missing
var_178numeric145236 unique values
0 missing
var_179numeric90091 unique values
0 missing
var_180numeric123477 unique values
0 missing
var_181numeric56164 unique values
0 missing
var_182numeric149196 unique values
0 missing
var_183numeric117529 unique values
0 missing
var_184numeric145185 unique values
0 missing
var_185numeric120747 unique values
0 missing
var_186numeric98060 unique values
0 missing
var_187numeric157031 unique values
0 missing
var_188numeric108813 unique values
0 missing
var_189numeric41765 unique values
0 missing
var_190numeric114959 unique values
0 missing
var_191numeric94266 unique values
0 missing
var_192numeric59066 unique values
0 missing
var_193numeric110557 unique values
0 missing
var_194numeric97069 unique values
0 missing
var_195numeric57870 unique values
0 missing
var_196numeric125560 unique values
0 missing
var_197numeric40537 unique values
0 missing
var_198numeric94153 unique values
0 missing
var_199numeric149430 unique values
0 missing
Show first 100 features

19 properties

NumberOfInstances
200000
Number of instances (rows) of the dataset.
NumberOfFeatures
202
Number of attributes (columns) of the dataset.
NumberOfClasses
2
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
200
Number of numeric attributes.
NumberOfSymbolicFeatures
2
Number of nominal attributes.
Dimensionality
0
Number of attributes divided by the number of instances.
PercentageOfNumericFeatures
99.01
Percentage of numeric attributes.
MajorityClassPercentage
89.95
Percentage of instances belonging to the most frequent class.
PercentageOfSymbolicFeatures
0.99
Percentage of nominal attributes.
MajorityClassSize
179902
Number of instances belonging to the most frequent class.
MinorityClassPercentage
10.05
Percentage of instances belonging to the least frequent class.
MinorityClassSize
20098
Number of instances belonging to the least frequent class.
NumberOfBinaryFeatures
1
Number of binary attributes.
PercentageOfBinaryFeatures
0.5
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
AutoCorrelation
0.82
Average class difference between consecutive instances.
PercentageOfMissingValues
0
Percentage of missing values.
Show all 19 properties

9 tasks

Supervised Classification on SantanderCustomerSatisfaction
0 runs - estimation_procedure: 20% Holdout (Ordered) - target_feature: target
Supervised Classification on SantanderCustomerSatisfaction
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: target
Clustering on SantanderCustomerSatisfaction
0 runs - estimation_procedure: 50 times Clustering
Clustering on SantanderCustomerSatisfaction
0 runs - estimation_procedure: 50 times Clustering
Clustering on SantanderCustomerSatisfaction
0 runs - estimation_procedure: 50 times Clustering
Clustering on SantanderCustomerSatisfaction
0 runs - estimation_procedure: 50 times Clustering
Clustering on SantanderCustomerSatisfaction
0 runs - estimation_procedure: 50 times Clustering
Clustering on SantanderCustomerSatisfaction
0 runs - estimation_procedure: 50 times Clustering
Clustering on SantanderCustomerSatisfaction
0 runs - estimation_procedure: 50 times Clustering
Define a new task