This project includes a Tensorflow implementation of a Multi-view Laplacian regularized DeepFM model for miRNA-disease association prediction
The code is for the Paper "MLRDFM: a multi-view Laplacian regularized DeepFM model for predicting miRNA-disease associations". If you use this code, please cite this paper.
Python 3.6.13
Tensorflow 1.14
numpy 1.17.0
scipy 1.5.2
This implementation requires the input data in the following format:
- Xi: [[ind1_1, ind1_2, ...], [ind2_1, ind2_2, ...], ..., [indi_1, indi_2, ..., indi_j, ...], ...]
- indi_j is the feature index of feature field j of sample i in the dataset
- Xv: [[val1_1, val1_2, ...], [val2_1, val2_2, ...], ..., [vali_1, vali_2, ..., vali_j, ...], ...]
- vali_j is the feature value of feature field j of sample i in the dataset
- vali_j can be either binary (1/0, for binary/categorical features) or float (e.g., 10.24, for numerical features)
- y: target of each sample in the dataset (1/0 for classification, numeric number for regression)