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torch.nn.modules.linear.Linear.a2f8be78ec8ad4d7
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torch.nn.modules.linear.Linear.a2f8be78ec8ad4d7
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Uploaded 18-11-2019 by
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torch==1.2.0 numpy>=1.6.1 scipy>=0.9
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openml-python
python
pytorch
torch_1.2.0
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Automatically created pytorch flow.
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out_features
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Supervised Classification
Supervised Regression
Learning Curve
Supervised Data Stream Classification
Clustering
Machine Learning Challenge
Survival Analysis
Subgroup Discovery
area under roc curve
average cost
binominal test
build cpu time
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class complexity
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confusion matrix
correlation coefficient
cortana quality
coverage
f measure
information gain
jaccard
kappa
kb relative information score
kohavi wolpert bias squared
kohavi wolpert error
kohavi wolpert sigma squared
kohavi wolpert variance
kononenko bratko information score
matthews correlation coefficient
mean absolute error
mean class complexity
mean class complexity gain
mean f measure
mean kononenko bratko information score
mean precision
mean prior absolute error
mean prior class complexity
mean recall
mean weighted area under roc curve
mean weighted f measure
mean weighted precision
weighted recall
number of instances
os information
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relative absolute error
root mean prior squared error
root mean squared error
root relative squared error
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scimark benchmark
single point area under roc curve
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usercpu time millis
usercpu time millis testing
usercpu time millis training
webb bias
webb error
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joint entropy
pattern team auroc10
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wall clock time millis testing
unweighted recall
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