aksnzhy / xlearn

High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.
https://xlearn-doc.readthedocs.io/en/latest/index.html
Apache License 2.0
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读取pandas数据训练loss为nan #353

Open nxgych opened 3 years ago

nxgych commented 3 years ago
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# DMatrix transition
xdm_train = xl.DMatrix(xtr, ytr)
xdm_test = xl.DMatrix(xte, yte)

# Training task
fm_model = xl.create_fm()  # Use factorization machine
fm_model.setOnDisk()
fm_model.setNoBin()
fm_model.setTrain(xdm_train)    # Training data
fm_model.setValidate(xdm_test)  # Validation data
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[ ACTION ] Start to train ... [------------] Epoch Train log_loss Test log_loss Test AUC Time cost (sec) [ 5% ] 1 -nan -nan 0.500000 2.51 [ 10% ] 2 -nan -nan 0.500000 2.90 [ 15% ] 3 -nan -nan 0.500000 2.50 [ 20% ] 4 -nan -nan 0.500000 2.89

kyle-pjk commented 3 years ago

一样遇到这个问题。。