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KDDCup09-Appetency

KDDCup09-Appetency

active ARFF Publicly available Visibility: public Uploaded 18-12-2020 by Marcos de Paula Bueno
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This is the full version of the KDD Cup 2009 dataset This Year's Challenge Customer Relationship Management (CRM) is a key element of modern marketing strategies. The KDD Cup 2009 offers the opportunity to work on large marketing databases from the French Telecom company Orange to predict the propensity of customers to switch provider (churn), buy new products or services (appetency), or buy upgrades or add-ons proposed to them to make the sale more profitable (up-selling). The most practical way, in a CRM system, to build knowledge on customer is to produce scores. A score (the output of a model) is an evaluation for all instances of a target variable to explain (i.e. churn, appetency or up-selling). Tools which produce scores allow to project, on a given population, quantifiable information. The score is computed using input variables which describe instances. Scores are then used by the information system (IS), for example, to personalize the customer relationship. An industrial customer analysis platform able to build prediction models with a very large number of input variables has been developed by Orange Labs. This platform implements several processing methods for instances and variables selection, prediction and indexation based on an efficient model combined with variable selection regularization and model averaging method. The main characteristic of this platform is its ability to scale on very large datasets with hundreds of thousands of instances and thousands of variables. The rapid and robust detection of the variables that have most contributed to the output prediction can be a key factor in a marketing application. The challenge is to beat the in-house system developed by Orange Labs. It is an opportunity to prove that you can deal with a very large database, including heterogeneous noisy data (numerical and categorical variables), and unbalanced class distributions. Time efficiency is often a crucial point. Therefore part of the competition will be time-constrained to test the ability of the participants to deliver solutions quickly. Task Description The task is to estimate the churn, appetency and up-selling probability of customers, hence there are three target values to be predicted. The challenge is staged in phases to test the rapidity with which each team is able to produce results. A large number of variables (15,000) is made available for prediction. However, to engage participants having access to less computing power, a smaller version of the dataset with only 230 variables will be made available in the second part of the challenge. * Churn (wikipedia definition): Churn rate is also sometimes called attrition rate. It is one of two primary factors that determine the steady-state level of customers a business will support. In its broadest sense, churn rate is a measure of the number of individuals or items moving into or out of a collection over a specific period of time. The term is used in many contexts, but is most widely applied in business with respect to a contractual customer base. For instance, it is an important factor for any business with a subscriber-based service model, including mobile telephone networks and pay TV operators. The term is also used to refer to participant turnover in peer-to-peer networks. * Appetency: In our context, the appetency is the propensity to buy a service or a product. * Up-selling (wikipedia definition): Up-selling is a sales technique whereby a salesman attempts to have the customer purchase more expensive items, upgrades, or other add-ons in an attempt to make a more profitable sale. Up-selling usually involves marketing more profitable services or products, but up-selling can also be simply exposing the customer to other options he or she may not have considered previously. Up-selling can imply selling something additional, or selling something that is more profitable or otherwise preferable for the seller instead of the original sale. The training set contains 50,000 examples. The first predictive 14,740 variables are numerical and the last 260 predictive variables are categorical. The last target variable is binary (-1,1).

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Var7178numeric3 unique values
0 missing
Var7434numeric19 unique values
0 missing
Var7690numeric2 unique values
0 missing
Var7946numeric1 unique values
0 missing
Var8202numeric1 unique values
0 missing
Var8458numeric13001 unique values
0 missing
Var8714numeric3 unique values
0 missing
Var8970numeric2 unique values
0 missing
Var9226numeric2 unique values
0 missing
Var9482numeric1 unique values
0 missing
Var9738numeric8 unique values
0 missing
Var9994numeric2 unique values
0 missing
Var10250numeric2 unique values
0 missing
Var10506numeric24 unique values
0 missing
Var10762numeric1 unique values
0 missing
Var11018numeric2 unique values
0 missing
Var11274numeric11 unique values
0 missing
Var11530numeric0 unique values
50000 missing
Var11786numeric2 unique values
0 missing
Var12042numeric2 unique values
0 missing
Var12298numeric2 unique values
0 missing
Var12554numeric98 unique values
0 missing
Var12810numeric2 unique values
0 missing
Var13066numeric1 unique values
0 missing
Var13322numeric1 unique values
0 missing
Var13578numeric2 unique values
0 missing
Var13834numeric2 unique values
0 missing
Var14090numeric2 unique values
0 missing
Var14346numeric2 unique values
0 missing
Var14602numeric2 unique values
0 missing
Var14858nominal1 unique values
0 missing
Var11numeric31 unique values
0 missing
Var267numeric1 unique values
0 missing
Var523numeric6 unique values
0 missing
Var779numeric4 unique values
0 missing
Var1035numeric2 unique values
0 missing
Var1291numeric2 unique values
0 missing
Var1547numeric9 unique values
0 missing
Var1803numeric2 unique values
0 missing
Var2059numeric2 unique values
0 missing
Var2315numeric46336 unique values
0 missing
Var2571numeric10 unique values
0 missing
Var2827numeric11 unique values
0 missing
Var3083numeric13 unique values
0 missing
Var3339numeric48620 unique values
0 missing
Var3595numeric3 unique values
0 missing
Var3851numeric2 unique values
0 missing
Var4107numeric1 unique values
0 missing
Var4363numeric50 unique values
0 missing
Var4619numeric23 unique values
0 missing
Var4875numeric6 unique values
0 missing
Var5131numeric14 unique values
0 missing
Var5387numeric24 unique values
0 missing
Var5643numeric23 unique values
0 missing
Var5899numeric40806 unique values
0 missing
Var6155numeric1 unique values
0 missing
Var6411numeric2 unique values
0 missing
Var6667numeric2 unique values
0 missing
Var6923numeric31071 unique values
0 missing
Var7179numeric1 unique values
0 missing
Var7435numeric1 unique values
0 missing
Var7691numeric9 unique values
0 missing
Var7947numeric10 unique values
0 missing
Var8203numeric2 unique values
0 missing
Var8459numeric24 unique values
0 missing
Var8715numeric2 unique values
0 missing
Var8971numeric2 unique values
0 missing
Var9227numeric2 unique values
0 missing
Var9483numeric2 unique values
0 missing
Var9739numeric23 unique values
0 missing
Var9995numeric2 unique values
0 missing
Var10251numeric9 unique values
0 missing
Var10507numeric2 unique values
0 missing
Var10763numeric23 unique values
0 missing
Var11019numeric3 unique values
0 missing
Var11275numeric1 unique values
0 missing
Var11531numeric4 unique values
48421 missing
Var11787numeric2 unique values
0 missing
Var12043numeric6 unique values
0 missing
Var12299numeric1 unique values
0 missing
Var12555numeric24 unique values
48513 missing
Var12811numeric18 unique values
0 missing
Var13067numeric13 unique values
0 missing
Var13323numeric1896 unique values
0 missing
Var13579numeric2 unique values
0 missing
Var13835numeric2 unique values
0 missing
Var14091numeric12 unique values
0 missing
Var14347numeric2 unique values
0 missing
Var14603numeric2 unique values
0 missing
Var14859nominal11 unique values
0 missing
Var12numeric3 unique values
0 missing
Var268numeric6 unique values
0 missing
Var524numeric124 unique values
0 missing
Var780numeric2 unique values
0 missing
Var1036numeric41287 unique values
0 missing
Var1292numeric2 unique values
0 missing
Var1548numeric1 unique values
0 missing
Var1804numeric9 unique values
0 missing
Var2060numeric11 unique values
0 missing
Var2316numeric2 unique values
0 missing
Var2572numeric22 unique values
0 missing
Var2828numeric1 unique values
0 missing
Var3084numeric14 unique values
0 missing
Var3340numeric9 unique values
0 missing
Var3596numeric7 unique values
0 missing
Var3852numeric12 unique values
0 missing
Var4108numeric279 unique values
0 missing
Var4364numeric65 unique values
0 missing
Var4620numeric2 unique values
0 missing
Var4876numeric17 unique values
0 missing
Var5132numeric119 unique values
0 missing
Var5388numeric1 unique values
0 missing
Var5644numeric12 unique values
0 missing
Var5900numeric36630 unique values
0 missing
Var6156numeric2 unique values
0 missing
Var6412numeric2 unique values
0 missing
Var6668numeric10 unique values
0 missing
Var6924numeric2 unique values
0 missing
Var7180numeric44462 unique values
0 missing
Var7436numeric2 unique values
0 missing
Var7692numeric5 unique values
0 missing
Var7948numeric1 unique values
0 missing
Var8204numeric26 unique values
0 missing
Var8460numeric2 unique values
0 missing
Var8716numeric6 unique values
0 missing
Var8972numeric12 unique values
0 missing
Var9228numeric1 unique values
0 missing
Var9484numeric19 unique values
0 missing
Var9740numeric1 unique values
0 missing
Var9996numeric2 unique values
0 missing
Var10252numeric10 unique values
0 missing
Var10508numeric2 unique values
0 missing
Var10764numeric78 unique values
0 missing
Var11020numeric3 unique values
0 missing
Var11276numeric4 unique values
0 missing
Var11532numeric2 unique values
0 missing
Var11788numeric1 unique values
0 missing
Var12044numeric4 unique values
0 missing
Var12300numeric1 unique values
0 missing
Var12556numeric2 unique values
0 missing
Var12812numeric2 unique values
0 missing
Var13068numeric1 unique values
0 missing
Var13324numeric2 unique values
0 missing
Var13580numeric2 unique values
0 missing
Var13836numeric21 unique values
0 missing
Var14092numeric132 unique values
0 missing
Var14348numeric2 unique values
0 missing
Var14604numeric2 unique values
0 missing
Var14860nominal4 unique values
0 missing
Var13numeric9 unique values
0 missing
Var269numeric0 unique values
50000 missing
Var525numeric25 unique values
0 missing
Var781numeric8 unique values
0 missing
Var1037numeric19 unique values
0 missing
Var1293numeric13 unique values
0 missing
Var1549numeric15 unique values
0 missing
Var1805numeric23 unique values
0 missing
Var2061numeric7 unique values
0 missing
Var2317numeric40 unique values
0 missing
Var2573numeric2 unique values
0 missing
Var2829numeric2 unique values
0 missing
Var3085numeric2 unique values
0 missing
Var3341numeric4 unique values
0 missing
Var3597numeric13 unique values
0 missing
Var3853numeric2 unique values
0 missing
Var4109numeric2 unique values
0 missing
Var4365numeric1 unique values
0 missing
Var4621numeric3 unique values
0 missing
Var4877numeric2 unique values
0 missing
Var5133numeric23 unique values
0 missing
Var5389numeric2 unique values
0 missing
Var5645numeric4 unique values
0 missing
Var5901numeric2 unique values
0 missing
Var6157numeric4 unique values
0 missing
Var6413numeric2 unique values
0 missing
Var6669numeric2 unique values
0 missing
Var6925numeric2 unique values
0 missing
Var7181numeric717 unique values
0 missing
Var7437numeric2 unique values
0 missing
Var7693numeric2 unique values
0 missing
Var7949numeric2 unique values
0 missing
Var8205numeric19 unique values
0 missing
Var8461numeric21 unique values
5011 missing
Var8717numeric48511 unique values
0 missing
Var8973numeric1 unique values
0 missing
Var9229numeric29099 unique values
0 missing
Var9485numeric2 unique values
0 missing
Var9741numeric36394 unique values
0 missing
Var9997numeric27794 unique values
0 missing
Var10253numeric2 unique values
0 missing
Var10509numeric9 unique values
0 missing
Var10765numeric7 unique values
0 missing
Var11021numeric22 unique values
0 missing
Var11277numeric38107 unique values
0 missing
Var11533numeric8 unique values
0 missing
Var11789numeric249 unique values
0 missing
Var12045numeric2 unique values
0 missing
Var12301numeric3 unique values
0 missing
Var12557numeric20 unique values
0 missing
Var12813numeric8 unique values
0 missing
Var13069numeric8 unique values
0 missing
Var13325numeric78 unique values
0 missing
Var13581numeric271 unique values
5009 missing
Var13837numeric1 unique values
0 missing
Var14093numeric3 unique values
0 missing
Var14349numeric1 unique values
0 missing
Var14605numeric2 unique values
0 missing
Var14861nominal1 unique values
0 missing
Var14numeric2 unique values
0 missing
Var270numeric26 unique values
0 missing
Var526numeric13 unique values
0 missing
Var782numeric14 unique values
0 missing
Var1038numeric3 unique values
0 missing
Var1294numeric99 unique values
0 missing
Var1550numeric257 unique values
0 missing
Var1806numeric23 unique values
0 missing
Var2062numeric26 unique values
0 missing
Var2318numeric23 unique values
0 missing
Var2574numeric23 unique values
0 missing
Var2830numeric3 unique values
0 missing
Var3086numeric22 unique values
0 missing
Var3342numeric7 unique values
0 missing
Var3598numeric2 unique values
0 missing
Var3854numeric2 unique values
0 missing
Var4110numeric2 unique values
0 missing
Var4366numeric2 unique values
0 missing
Var4622numeric2 unique values
0 missing
Var4878numeric25 unique values
0 missing
Var5134numeric222 unique values
0 missing
Var5390numeric2 unique values
0 missing
Var5646numeric49 unique values
0 missing
Var5902numeric2 unique values
0 missing
Var6158numeric3 unique values
0 missing
Var6414numeric22 unique values
0 missing
Var6670numeric2 unique values
0 missing
Var6926numeric2 unique values
0 missing
Var7182numeric52 unique values
0 missing
Var7438numeric2 unique values
0 missing
Var7694numeric210 unique values
0 missing
Var7950numeric227 unique values
0 missing
Var8206numeric2 unique values
0 missing
Var8462numeric2 unique values
0 missing
Var8718numeric1 unique values
0 missing
Var8974numeric80 unique values
0 missing
Var9230numeric13 unique values
0 missing
Var9486numeric2 unique values
0 missing
Var9742numeric1 unique values
0 missing
Var9998numeric22 unique values
0 missing
Var10254numeric15 unique values
0 missing
Var10510numeric2 unique values
0 missing
Var10766numeric116 unique values
0 missing
Var11022numeric26 unique values
0 missing
Var11278numeric1149 unique values
0 missing
Var11534numeric2 unique values
0 missing
Var11790numeric1157 unique values
0 missing
Var12046numeric2 unique values
0 missing
Var12302numeric44177 unique values
0 missing
Var12558numeric1 unique values
48759 missing
Var12814numeric8 unique values
0 missing
Var13070numeric2 unique values
0 missing
Var13326numeric2 unique values
0 missing
Var13582numeric138 unique values
0 missing
Var13838numeric26 unique values
0 missing
Var14094numeric1 unique values
0 missing
Var14350numeric1 unique values
0 missing
Var14606numeric35 unique values
49180 missing
Var14862nominal13 unique values
0 missing
Var15numeric1 unique values
0 missing
Var271numeric103 unique values
0 missing
Var527numeric12 unique values
0 missing
Var783numeric9 unique values
0 missing
Var1039numeric2 unique values
0 missing
Var1295numeric2 unique values
0 missing
Var1551numeric1 unique values
0 missing
Var1807numeric21 unique values
0 missing
Var2063numeric25 unique values
0 missing
Var2319numeric285 unique values
0 missing
Var2575numeric24 unique values
0 missing
Var2831numeric263 unique values
0 missing
Var3087numeric16 unique values
0 missing
Var3343numeric2 unique values
0 missing
Var3599numeric3 unique values
0 missing
Var3855numeric1 unique values
0 missing
Var4111numeric118 unique values
0 missing
Var4367numeric767 unique values
0 missing
Var4623numeric15 unique values
0 missing
Var4879numeric2 unique values
0 missing
Var5135numeric0 unique values
50000 missing
Var5391numeric2 unique values
0 missing
Var5647numeric5 unique values
0 missing
Var5903numeric2 unique values
0 missing
Var6159numeric41932 unique values
0 missing
Var6415numeric2 unique values
0 missing
Var6671numeric44396 unique values
0 missing
Var6927numeric2 unique values
0 missing
Var7183numeric22 unique values
0 missing
Var7439numeric1 unique values
0 missing
Var7695numeric2 unique values
0 missing
Var7951numeric2 unique values
0 missing
Var8207numeric2 unique values
0 missing
Var8463numeric2 unique values
0 missing
Var8719numeric2 unique values
0 missing
Var8975numeric2 unique values
0 missing
Var9231numeric2 unique values
0 missing
Var9487numeric2 unique values
0 missing
Var9743numeric8 unique values
0 missing
Var9999numeric82 unique values
0 missing
Var10255numeric2 unique values
0 missing
Var10511numeric130 unique values
0 missing
Var10767numeric1161 unique values
0 missing
Var11023numeric20 unique values
0 missing
Var11279numeric18 unique values
0 missing
Var11535numeric5 unique values
0 missing
Var11791numeric2 unique values
0 missing
Var12047numeric2 unique values
0 missing
Var12303numeric127 unique values
0 missing
Var12559numeric2 unique values
0 missing
Var12815numeric6 unique values
0 missing
Var13071numeric28 unique values
0 missing
Var13327numeric2 unique values
0 missing
Var13583numeric24 unique values
0 missing
Var13839numeric77 unique values
0 missing
Var14095numeric3 unique values
0 missing
Var14351numeric1 unique values
0 missing
Var14607numeric2 unique values
0 missing
Var14863nominal6 unique values
0 missing
Var16numeric2 unique values
0 missing
Var272numeric187 unique values
0 missing
Var528numeric1 unique values
0 missing
Var784numeric4 unique values
0 missing
Var1040numeric69 unique values
0 missing
Var1296numeric867 unique values
0 missing
Var1552numeric20 unique values
0 missing
Var1808numeric13 unique values
5009 missing
Var2064numeric26 unique values
0 missing
Var2320numeric2 unique values
0 missing
Var2576numeric1 unique values
0 missing
Var2832numeric2 unique values
0 missing
Var3088numeric1 unique values
0 missing
Var3344numeric2 unique values
0 missing
Var3600numeric4 unique values
0 missing
Var3856numeric2 unique values
0 missing
Var4112numeric1 unique values
0 missing
Var4368numeric2 unique values
0 missing
Var4624numeric2 unique values
0 missing
Var4880numeric2 unique values
0 missing
Var5136numeric14 unique values
0 missing
Var5392numeric2 unique values
0 missing
Var5648numeric2 unique values
0 missing
Var5904numeric10 unique values
0 missing
Var6160numeric9 unique values
0 missing
Var6416numeric2 unique values
0 missing
Var6672numeric2 unique values
0 missing
Var6928numeric2 unique values
0 missing
Var7184numeric10 unique values
0 missing
Var7440numeric1 unique values
0 missing
Var7696numeric28240 unique values
0 missing
Var7952numeric25 unique values
0 missing
Var8208numeric22 unique values
0 missing
Var8464numeric2 unique values
0 missing
Var8720numeric2 unique values
0 missing
Var8976numeric26 unique values
49306 missing
Var9232numeric9 unique values
0 missing
Var9488numeric2 unique values
0 missing
Var9744numeric13 unique values
0 missing
Var10000numeric2 unique values
0 missing
Var10256numeric82 unique values
24548 missing
Var10512numeric5 unique values
0 missing
Var10768numeric61 unique values
0 missing
Var11024numeric48 unique values
0 missing
Var11280numeric2 unique values
0 missing
Var11536numeric2 unique values
0 missing
Var11792numeric2 unique values
0 missing
Var12048numeric2 unique values
0 missing
Var12304numeric551 unique values
0 missing
Var12560numeric5 unique values
0 missing
Var12816numeric2 unique values
0 missing
Var13072numeric1 unique values
0 missing
Var13328numeric23 unique values
0 missing
Var13584numeric2 unique values
0 missing
Var13840numeric402 unique values
0 missing
Var14096numeric2 unique values
0 missing
Var14352numeric21 unique values
0 missing
Var14608numeric2 unique values
0 missing
Var14864nominal1 unique values
0 missing
Var17numeric20 unique values
0 missing
Var273numeric18149 unique values
0 missing
Var529numeric7 unique values
0 missing
Var785numeric864 unique values
0 missing
Var1041numeric1 unique values
0 missing
Var1297numeric1 unique values
0 missing
Var1553numeric1 unique values
0 missing
Var1809numeric1 unique values
0 missing
Var2065numeric1 unique values
0 missing
Var2321numeric20 unique values
0 missing
Var2577numeric12 unique values
0 missing
Var2833numeric2 unique values
0 missing
Var3089numeric7 unique values
0 missing
Var3345numeric8 unique values
0 missing
Var3601numeric1 unique values
0 missing
Var3857numeric29 unique values
0 missing
Var4113numeric1 unique values
0 missing
Var4369numeric1 unique values
0 missing
Var4625numeric18 unique values
0 missing
Var4881numeric15 unique values
0 missing
Var5137numeric2 unique values
0 missing
Var5393numeric71 unique values
0 missing
Var5649numeric1 unique values
0 missing
Var5905numeric1 unique values
0 missing
Var6161numeric26 unique values
0 missing
Var6417numeric2 unique values
0 missing
Var6673numeric2 unique values
0 missing
Var6929numeric1 unique values
0 missing
Var7185numeric200 unique values
0 missing
Var7441numeric5 unique values
0 missing
Var7697numeric9 unique values
0 missing
Var7953numeric2 unique values
0 missing
Var8209numeric2 unique values
0 missing
Var8465numeric19 unique values
0 missing
Var8721numeric18 unique values
0 missing
Var8977numeric6 unique values
0 missing
Var9233numeric157 unique values
0 missing
Var9489numeric4 unique values
0 missing
Var9745numeric99 unique values
0 missing
Var10001numeric2 unique values
0 missing
Var10257numeric2 unique values
0 missing
Var10513numeric41207 unique values
0 missing
Var10769numeric715 unique values
0 missing
Var11025numeric15 unique values
0 missing
Var11281numeric34888 unique values
0 missing
Var11537numeric2 unique values
0 missing
Var11793numeric5 unique values
0 missing
Var12049numeric152 unique values
0 missing
Var12305numeric2 unique values
0 missing
Var12561numeric5 unique values
0 missing
Var12817numeric1 unique values
0 missing
Var13073numeric3 unique values
0 missing
Var13329numeric4 unique values
0 missing
Var13585numeric2 unique values
0 missing
Var13841numeric237 unique values
0 missing

19 properties

50000
Number of instances (rows) of the dataset.
15001
Number of attributes (columns) of the dataset.
2
Number of distinct values of the target attribute (if it is nominal).
14616450
Number of missing values in the dataset.
50000
Number of instances with at least one value missing.
14740
Number of numeric attributes.
261
Number of nominal attributes.
0.21
Percentage of binary attributes.
100
Percentage of instances having missing values.
1.95
Percentage of missing values.
0.96
Average class difference between consecutive instances.
98.26
Percentage of numeric attributes.
0.3
Number of attributes divided by the number of instances.
1.74
Percentage of nominal attributes.
98.22
Percentage of instances belonging to the most frequent class.
49110
Number of instances belonging to the most frequent class.
1.78
Percentage of instances belonging to the least frequent class.
890
Number of instances belonging to the least frequent class.
32
Number of binary attributes.

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