Name | Description | |
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iteration_length | One iteration is iteration_length * number of entries in the training matrix |
Name | Description | |
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BPR_Linear | There is no summary. |
Name | Description | |
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ComputeFit | There is no summary. |
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Iterate | Perform one iteration of stochastic gradient ascent over the training data. One iteration is iteration_length * number of entries in the training matrix |
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LoadModel | There is no summary. |
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Predict | There is no summary. |
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SaveModel | There is no summary. |
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ToString | There is no summary. |
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Train | There is no summary. |
Name | Description | |
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SampleItemPair | Sample a pair of items, given a user |
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SampleTriple | Sample a triple for BPR learning |
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SampleUser | Sample a user that has viewed at least one and not all items |
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UpdateFeatures | Modified feature update method that exploits attribute sparsity |
Name | Description | |
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FastSamplingMemoryLimit | Fast sampling memory limit, in MiB |
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InitMean | mean of the Gaussian distribution used to initialize the features |
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InitStdev | standard deviation of the normal distribution used to initialize the features |
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ItemAttributes | There is no summary. |
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LearnRate | Learning rate alpha |
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NumItemAttributes | There is no summary. |
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NumIter | Number of iterations over the training data |
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Regularization | Regularization parameter |