Fig. 2From: A learning-based method for drug-target interaction prediction based on feature representation learning and deep neural networkThe schematic illustration of denoising autoencoder. The original input data is high-dimensional, noisy and incomplete, the DAE adds noise to it and makes the self-encoder learn to remove the noise, which makes the encoder learn more robust and low-dimensional representation in the input data. Then the decoder is used to recover the original input from low-dimensional data, the loss between the original input and the decoder output is optimized by the RMSProp algorithmBack to article page