Willing Chen

读取pandas数据训练loss为nan

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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) #...

libsvm 格式的数据训练Segmentation fault，同样的数据用libfm可以正常训练

how to generate 256 dimensions of feature vector?

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I wanna get 256 dimensions of feature vector, how to generate that?

FFMModel 如何使用呢

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请教下：ffm模型的sklearn API - FFMModel 如何使用呢