Data
bank-marketing

bank-marketing

active ARFF Publicly available Visibility: public Uploaded 27-01-2023 by Young Lee
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The data is related with direct marketing campaigns of a Portuguese banking institution. The marketing campaigns were based on phone calls. Often, more than one contact to the same client was required, in order to access if the product (bank term deposit) would be (or not) subscribed.The classification goal is to predict if the client will subscribe a term deposit (variable y).

17 features

class (target)numeric2 unique values
0 missing
V1numeric77 unique values
0 missing
V6numeric7168 unique values
0 missing
V10numeric31 unique values
0 missing
V12numeric1573 unique values
0 missing
V13numeric48 unique values
0 missing
V14numeric559 unique values
0 missing
V15numeric41 unique values
0 missing
V2nominal12 unique values
0 missing
V3nominal3 unique values
0 missing
V4nominal4 unique values
0 missing
V5nominal2 unique values
0 missing
V7nominal2 unique values
0 missing
V8nominal2 unique values
0 missing
V9nominal3 unique values
0 missing
V11nominal12 unique values
0 missing
V16nominal4 unique values
0 missing

19 properties

45211
Number of instances (rows) of the dataset.
17
Number of attributes (columns) of the dataset.
0
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
8
Number of numeric attributes.
9
Number of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
3
Number of binary attributes.
17.65
Percentage of binary attributes.
0
Percentage of instances having missing values.
1
Average class difference between consecutive instances.
0
Percentage of missing values.
0
Number of attributes divided by the number of instances.
47.06
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
52.94
Percentage of nominal attributes.

1 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
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