Data
dresses-sales

dresses-sales

active ARFF Publicly available Visibility: public Uploaded 27-01-2023 by Young Lee
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  • Computational Universe Computer Systems
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This dataset contain attributes of dresses and their recommendations according to their sales. Sales are monitor on the basis of alternate days.The attributes present analyzed are: Recommendation, Style, Price, Rating, Size, Season, NeckLine, SleeveLength, waiseline, Material, FabricType, Decoration, Pattern, Type. In this dataset they are named Class(target) and then subsequently V2 - V13.Contact:Muhammad Usman & Adeel Ahmed, usman.madspot '@' gmail.com adeel.ahmed92 '@' gmail.com, Air University, Students at Air University.

13 features

class (target)numeric2 unique values
0 missing
V4numeric17 unique values
0 missing
V2nominal13 unique values
0 missing
V3nominal8 unique values
0 missing
V5nominal7 unique values
0 missing
V6nominal9 unique values
0 missing
V7nominal17 unique values
0 missing
V8nominal18 unique values
0 missing
V9nominal5 unique values
0 missing
V10nominal24 unique values
0 missing
V11nominal23 unique values
0 missing
V12nominal25 unique values
0 missing
V13nominal15 unique values
0 missing

19 properties

500
Number of instances (rows) of the dataset.
13
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.
2
Number of numeric attributes.
11
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.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0.96
Average class difference between consecutive instances.
0
Percentage of missing values.
0.03
Number of attributes divided by the number of instances.
15.38
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
84.62
Percentage of nominal attributes.

1 tasks

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