Features

Feature Columns

SparseFeat

SparseFeat is a namedtuple with signature SparseFeat(name, vocabulary_size, embedding_dim, use_hash, dtype,embedding_name, group_name)

• name : feature name

• vocabulary_size : number of unique feature values for sprase feature or hashing space when use_hash=True

• embedding_dim : embedding dimension

• use_hash : defualt False.If True the input will be hashed to space of size vocabulary_size.

• dtype : default float32.dtype of input tensor.

• embedding_name : default None. If None, the embedding_name will be same as name.

• group_name : feature group of this feature.

DenseFeat

DenseFeat is a namedtuple with signature DenseFeat(name, dimension, dtype)

• name : feature name

• dimension : dimension of dense feature vector.

• dtype : default float32.dtype of input tensor.

VarLenSparseFeat

VarLenSparseFeat is a namedtuple with signature VarLenSparseFeat(sparsefeat, maxlen, combiner, length_name, weight_name,weight_norm)

• sparsefeat : a instance of SparseFeat

• maxlen : maximum length of this feature for all samples

• combiner : pooling method,can be sum,mean or max

• length_name : feature length name,if None, value 0 in feature is for padding.

• weight_name : default None. If not None, the sequence feature will be multiplyed by the feature whose name is weight_name.

• weight_norm : default True. Whether normalize the weight score or not.

Models

FM (Convolutional Click Prediction Model)

FM Model API

Factorization Machines

DSSM (Deep Structured Semantic Model)

DSSM Model API

DSSM

Deep Structured Semantic Models for Web Search using Clickthrough Data

YoutubeDNN

YoutubeDNN Model API

YoutubeDNN

Deep Neural Networks for YouTube Recommendations

NCF (Neural Collaborative Filtering)

NCF Model API

NCF

Neural Collaborative Filtering

MIND (Multi-Interest Network with Dynamic routing)

MIND Model API

MIND

Multi-interest network with dynamic routing for recommendation at Tmall