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Cervical Cancer Behavior Risk Data Set
Download: Data Folder, Data Set Description

Abstract: The dataset contains 19 attributes regarding ca cervix behavior risk with class label is ca_cervix with 1 and 0 as values which means the respondent with and without ca cervix, respectively.

Data Set Characteristics:  

Multivariate, Univariate

Number of Instances:

72

Area:

Life

Attribute Characteristics:

Integer

Number of Attributes:

19

Date Donated

2019-07-17

Associated Tasks:

Classification, Clustering

Missing Values?

N/A

Number of Web Hits:

19569


Source:

Name: DR. Sobar
Institution: STIKES Indonesia Maju, Jakarta, Indonesia
Email: sobar2000 '@' gmail.com

Name: Prof. Rizanda Machmud
Institution: Universitas Andalas, Padang, Indonesia
Email: rizandamachmud '@' fk.unand.ac.id

Name: Adi Wijaya, PhD candidate
Institution: STIKES Indonesia Maju
Email: adiwjj '@' stikim.ac.id


Data Set Information:

Provide all relevant information about your data set.


Attribute Information:

This dataset consist of 18 attribute (comes from 8 variables, the name of variables is the first word in each attribute)
1) behavior_eating
2) behavior_personalHygine
3) intention_aggregation
4) intention_commitment
5) attitude_consistency
6) attitude_spontaneity
7) norm_significantPerson
8) norm_fulfillment
9) perception_vulnerability
10) perception_severity
11) motivation_strength
12) motivation_willingness
13) socialSupport_emotionality
14) socialSupport_appreciation
15) socialSupport_instrumental
16) empowerment_knowledge
17) empowerment_abilities
18) empowerment_desires
19) ca_cervix (this is class attribute, 1=has cervical cancer, 0=no cervical cancer)


Relevant Papers:

Sobar, Machmud, R., & Wijaya, A. (2016). Behavior Determinant Based Cervical Cancer Early Detection with Machine Learning Algorithm. Advanced Science Letters, 22(10), 3120–3123. [Web Link]



Citation Request:

Sobar, Machmud, R., & Wijaya, A. (2016). Behavior Determinant Based Cervical Cancer Early Detection with Machine Learning Algorithm. Advanced Science Letters, 22(10), 3120–3123. [Web Link]


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