Data
CSM

CSM

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Author: Mehreen Ahmed Source: [original](http://archive.ics.uci.edu/ml/datasets/CSM+(Conventional+and+Social+Media+Movies)+Dataset+2014+and+2015#) - Date unknown Please cite: Conventional and Social Media Movies (CSM) - Dataset 2014 and 2015 Data Set 12 features categorized as conventional and social media features. Both conventional features, collected from movies databases on Web as well as social media features(YouTube,Twitter).

14 features

Movienominal231 unique values
1 missing
Yearnumeric2 unique values
1 missing
Ratingsnumeric45 unique values
1 missing
Genrenumeric11 unique values
1 missing
Grossnumeric215 unique values
1 missing
Budgetnumeric104 unique values
2 missing
Screensnumeric200 unique values
11 missing
Sequelnumeric7 unique values
1 missing
Sentimentnumeric36 unique values
1 missing
Viewsnumeric231 unique values
1 missing
Likesnumeric227 unique values
1 missing
Dislikesnumeric203 unique values
1 missing
Commentsnumeric213 unique values
1 missing
Aggregate.Followersnumeric190 unique values
36 missing

19 properties

232
Number of instances (rows) of the dataset.
14
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
60
Number of missing values in the dataset.
45
Number of instances with at least one value missing.
13
Number of numeric attributes.
1
Number of nominal attributes.
0.06
Number of attributes divided by the number of instances.
92.86
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
7.14
Percentage 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.
19.4
Percentage of instances having missing values.
Average class difference between consecutive instances.
1.85
Percentage of missing values.

7 tasks

0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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