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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2085

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2085

deactivated ARFF Publicly available Visibility: public Uploaded 15-07-2016 by Noureddin Sadawi
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This dataset contains QSAR data (from ChEMBL version 17) showing activity values (unit is pseudo-pCI50) of several compounds on drug target ChEMBL_ID: CHEMBL2085 (TID: 10200), and it has 172 rows and 65 features (not including molecule IDs and class feature: molecule_id and pXC50). The features represent Molecular Descriptors which were generated from SMILES strings. Missing value imputation was applied to this dataset (By choosing the Median). Feature selection was also applied.

67 features

pXC50 (target)numeric111 unique values
0 missing
molecule_id (row identifier)nominal172 unique values
0 missing
Eta_alpha_Anumeric63 unique values
0 missing
Minumeric54 unique values
0 missing
ATSC1enumeric108 unique values
0 missing
P_VSA_i_4numeric46 unique values
0 missing
BIC1numeric106 unique values
0 missing
C.031numeric2 unique values
0 missing
IC1numeric135 unique values
0 missing
Eta_betaS_Anumeric64 unique values
0 missing
BIC2numeric98 unique values
0 missing
P_VSA_v_2numeric97 unique values
0 missing
SAaccnumeric94 unique values
0 missing
Mpnumeric93 unique values
0 missing
ATSC3enumeric143 unique values
0 missing
P_VSA_e_2numeric150 unique values
0 missing
P_VSA_p_3numeric150 unique values
0 missing
P_VSA_v_3numeric150 unique values
0 missing
SsssCHnumeric72 unique values
0 missing
Menumeric57 unique values
0 missing
PW5numeric47 unique values
0 missing
P_VSA_s_6numeric89 unique values
0 missing
nHetnumeric9 unique values
0 missing
BLInumeric117 unique values
0 missing
X1Avnumeric77 unique values
0 missing
ATSC5enumeric149 unique values
0 missing
P_VSA_LogP_5numeric98 unique values
0 missing
SpAD_EA.dm.numeric81 unique values
0 missing
SpDiam_EA.ed.numeric129 unique values
0 missing
MATS3enumeric123 unique values
0 missing
Eta_epsi_Anumeric99 unique values
0 missing
AACnumeric113 unique values
0 missing
AECCnumeric123 unique values
0 missing
ALOGPnumeric150 unique values
0 missing
ALOGP2numeric151 unique values
0 missing
AMRnumeric152 unique values
0 missing
AMWnumeric131 unique values
0 missing
ARRnumeric53 unique values
0 missing
ATS1enumeric131 unique values
0 missing
ATS1inumeric131 unique values
0 missing
ATS1mnumeric128 unique values
0 missing
ATS1pnumeric127 unique values
0 missing
ATS1snumeric138 unique values
0 missing
ATS1vnumeric133 unique values
0 missing
ATS2enumeric133 unique values
0 missing
ATS2inumeric137 unique values
0 missing
ATS2mnumeric135 unique values
0 missing
ATS2pnumeric143 unique values
0 missing
ATS2snumeric148 unique values
0 missing
ATS2vnumeric141 unique values
0 missing
ATS3enumeric145 unique values
0 missing
ATS3inumeric143 unique values
0 missing
ATS3mnumeric152 unique values
0 missing
ATS3pnumeric144 unique values
0 missing
ATS3snumeric155 unique values
0 missing
ATS3vnumeric148 unique values
0 missing
ATS4enumeric150 unique values
0 missing
ATS4inumeric148 unique values
0 missing
ATS4mnumeric154 unique values
0 missing
ATS4pnumeric155 unique values
0 missing
ATS4snumeric150 unique values
0 missing
ATS4vnumeric150 unique values
0 missing
ATS5enumeric157 unique values
0 missing
ATS5inumeric155 unique values
0 missing
ATS5mnumeric151 unique values
0 missing
ATS5pnumeric153 unique values
0 missing
ATS5snumeric149 unique values
0 missing

62 properties

172
Number of instances (rows) of the dataset.
67
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.
66
Number of numeric attributes.
1
Number of nominal attributes.
1.34
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.39
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
3.61
Second quartile (Median) of means among attributes of the numeric type.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
0.65
Mean skewness among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Percentage of instances belonging to the most frequent class.
4.46
Mean standard deviation of attributes of the numeric type.
0.5
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0
Percentage of binary attributes.
0.27
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-0.83
Minimum kurtosis among attributes of the numeric type.
-0.14
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
10.21
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
2.57
Third quartile of kurtosis among attributes of the numeric type.
107
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
98.51
Percentage of numeric attributes.
5.47
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-0.63
Minimum skewness among attributes of the numeric type.
1.49
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
The maximum number of distinct values among attributes of the nominal type.
0.01
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.94
Third quartile of skewness among attributes of the numeric type.
3.24
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0.62
First quartile of kurtosis among attributes of the numeric type.
0.86
Third quartile of standard deviation of attributes of the numeric type.
36.27
Maximum standard deviation of attributes of the numeric type.
Number of instances belonging to the least frequent class.
0.99
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
Average entropy of the attributes.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
1.87
Mean kurtosis among attributes of the numeric type.
0.22
First quartile of skewness among attributes of the numeric type.
14.55
Mean of means among attributes of the numeric type.
0.2
First quartile of standard deviation of attributes of the numeric type.
0.33
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
Second quartile (Median) of entropy among attributes.
Entropy of the target attribute values.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.

12 tasks

2 runs - estimation_procedure: Custom 10-fold Crossvalidation - target_feature: pXC50
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
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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