Data
Bioresponse

Bioresponse

active ARFF Publicly available Visibility: public Uploaded 03-01-2023 by Leo Grin
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Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "classification on numerical features" benchmark. Original link: https://openml.org/d/4134 Original description: Author: Boehringer Ingelheim Source: [Kaggle](https://www.kaggle.com/c/bioresponse) - 2011 Please cite: None Predict a biological response of molecules from their chemical properties. Each row in this data set represents a molecule. The first column contains experimental data describing an actual biological response; the molecule was seen to elicit this response (1), or not (0). The remaining columns represent molecular descriptors (d1 through d1776), these are calculated properties that can capture some of the characteristics of the molecule - for example size, shape, or elemental constitution. The descriptor matrix has been normalized. The original training and test set were merged.

420 features

target (target)numeric2 unique values
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D415numeric12 unique values
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D416numeric21 unique values
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D417numeric16 unique values
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D418numeric15 unique values
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D419numeric16 unique values
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D420numeric16 unique values
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D422numeric14 unique values
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D423numeric13 unique values
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D424numeric14 unique values
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19 properties

3434
Number of instances (rows) of the dataset.
420
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.
420
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
1
Average class difference between consecutive instances.
100
Percentage of numeric attributes.
0.12
Number of attributes divided by the number of instances.
0
Percentage of nominal attributes.
Percentage of instances belonging to the most frequent class.
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.

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