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breast-cancer-coimbra

breast-cancer-coimbra

active ARFF CC-BY Visibility: public Uploaded 19-05-2021 by Meilina Reksoprodjo
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Author: Miguel Patricio, Jose Pereira, Joana Crisostomo, Paulo Matafome, Raquel Seica, Francisco Caramelo Source: [UCI](https://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Coimbra) - 2018 Please cite: [Paper](doi:10.1186/s12885-017-3877-1 Heart failure clinical records dataset Breast cancer coimbra dataset There are 10 predictors, all quantitative, and a binary dependent variable, indicating the presence or absence of breast cancer. The predictors are anthropometric data and parameters which can be gathered in routine blood analysis. Prediction models based on these predictors, if accurate, can potentially be used as a biomarker of breast cancer. ### Attribute information Quantitative Attributes: - Age (years) - BMI (kg/m2) - Glucose (mg/dL) - Insulin (microgram/mL) - HOMA - Leptin (ng/mL) - Adiponectin (microg/mL) - Resistin (ng/mL) - MCP-1(pg/dL) Labels: 1. Healthy controls 2. Patients

10 features

Classification (target)numeric2 unique values
0 missing
Agenumeric51 unique values
0 missing
BMInumeric110 unique values
0 missing
Glucosenumeric50 unique values
0 missing
Insulinnumeric113 unique values
0 missing
HOMAnumeric116 unique values
0 missing
Leptinnumeric116 unique values
0 missing
Adiponectinnumeric115 unique values
0 missing
Resistinnumeric116 unique values
0 missing
MCP.1numeric113 unique values
0 missing
Show all 10 features

19 properties

NumberOfInstances
116
Number of instances (rows) of the dataset.
NumberOfFeatures
10
Number of attributes (columns) of the dataset.
NumberOfClasses
0
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
10
Number of numeric attributes.
NumberOfSymbolicFeatures
0
Number of nominal attributes.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
AutoCorrelation
0.99
Average class difference between consecutive instances.
PercentageOfNumericFeatures
100
Percentage of numeric attributes.
Dimensionality
0.09
Number of attributes divided by the number of instances.
PercentageOfSymbolicFeatures
0
Percentage of nominal attributes.
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
MajorityClassSize
Number of instances belonging to the most frequent class.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
MinorityClassSize
Number of instances belonging to the least frequent class.
NumberOfBinaryFeatures
0
Number of binary attributes.
Show all 19 properties

1 tasks

Supervised Regression on breast-cancer-coimbra
0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Classification
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