SHIFT15M: multiobjective large-scale fashion dataset with distributional shifts

Related tags

Deep Learningmachine-learningresearchdeep-learningfashiondatasetdatasetscovariate-shiftfill-in-the-blankdataset-shiftsdistributional-shifttarget-shiftset-matchingfill-in-the-n-blank
Overview

License: MIT Python GitHub code size in bytes Downloads GitHub Workflow Status PyPI version GitHub issues GitHub commit activity GitHub last commit arXiv

[arXiv]

The main motivation of the SHIFT15M project is to provide a dataset that contains natural dataset shifts collected from a web service IQON, which was actually in operation for a decade. In addition, the SHIFT15M dataset has several types of dataset shifts, allowing us to evaluate the robustness of the model to different types of shifts (e.g., covariate shift and target shift).

We provide the Datasheet for SHIFT15M. This datasheet is based on the Datasheets for Datasets [1] template.

System Python 3.6 Python 3.7 Python 3.8
Linux CPU
Linux GPU
Windows CPU / GPU Status Currently Unavailable Status Currently Unavailable Status Currently Unavailable
Mac OS CPU

SHIFT15M is a large-scale dataset based on approximately 15 million items accumulated by the fashion search service IQON.

Installation

From PyPi

$ pip install shift15m

From source

$ git clone https://github.com/st-tech/zozo-shift15m.git
$ cd zozo-shift15m
$ poetry build
$ pip install dist/shift15m-xxxx-py3-none-any.whl

Download SHIFT15M dataset

Use Dataset class

You can download SHIFT15M dataset as follows:

from shift15.datasets import NumLikesRegression

dataset = NumLikesRegression(root="./data", download=True)

Download directly by using download scripts

Please download the dataset as follows:

$ bash scripts/download_all.sh

To avoid downloading the test dataset for set matching (80GB), which is not required in training, you can use the following script.

$ bash scripts/download_all_wo_set_testdata.sh

Tasks

The following tasks are now available:

Tasks Task type Shift type # of input dim # of output dim
NumLikesRegression regression target shift (N, 25) (N, 1)
SumPricesRegression regression covariate shift, target shift (N, 1) (N, 1)
ItemPriceRegression regression target shift (N, 4096) (N, 1)
ItemCategoryClassification classification target shift (N, 4096) (N, 7)
Set2SetMatching set-to-set matching covariate shift (N, 4096)x(M, 4096) (1)

Benchmarks

As templates for numerical experiments on the SHIFT15M dataset, we have published experimental results for each task with several models.

Original Dataset Structure

The original dataset is maintained in json format, and a row consists of the following:

{
  "user":{"user_id":"xxxx", "fav_brand_ids":"xxxx,xx,..."},
  "like_num":"xx",
  "set_id":"xxx",
  "items":[
    {"price":"xxxx","item_id":"xxxxxx","category_id1":"xx","category_id2":"xxxxx"},
    ...
  ],
  "publish_date":"yyyy-mm-dd"
}

Contributing

To learn more about making a contribution to SHIFT15M, please see the following materials:

License

The dataset itself is provided under a CC BY-NC 4.0 license. On the other hand, the software in this repository is provided under the MIT license.

Dataset metadata

The following table is necessary for this dataset to be indexed by search engines such as Google Dataset Search.

property value
name SHIFT15M Dataset
alternateName SHIFT15M
alternateName shift15m-dataset
url
sameAs https://github.com/st-tech/zozo-shift15m
description SHIFT15M is a multi-objective, multi-domain dataset which includes multiple dataset shifts.
provider
property value
name ZOZO Research
sameAs https://ja.wikipedia.org/wiki/ZOZO
license
property value
name CC BY-NC 4.0
url

Citation

@misc{Kimura_SHIFT15M_Multiobjective_LargeScale_2021,
author = {Kimura, Masanari and Nakamura, Takuma and Saito, Yuki},
month = {8},
title = {SHIFT15M: Multiobjective Large-Scale Fashion Dataset with Distributional Shifts},
year = {2021}
}

Errata

No errata are currently available.

References

  • [1] Gebru, Timnit, et al. "Datasheets for datasets." arXiv preprint arXiv:1803.09010 (2018).
Comments
Releases(v0.2.0)

  • v0.2.0(Sep 20, 2022)

    • add tags info as follows:
    {
  "user":{"user_id":"xxxx", "fav_brand_ids":"xxxx,xx,..."},
  "like_num":"xx",
  "set_id":"xxx",
  "items":[
    {"price":"xxxx","item_id":"xxxxxx","category_id1":"xx","category_id2":"xxxxx"},
    ...
  ],
  "publish_date":"yyyy-mm-dd",
  "tags": "tag_a, tag_b, tag_c, ..."
}
    • add superset matching benchmark
    • fix a label creation bug on set matching with multiple splits
    Source code(tar.gz)
    Source code(zip)

  • v.0.1.2(Nov 24, 2021)

  • v.0.1.1(Sep 6, 2021)

Owner
ZOZO, Inc.
ZOZO, Inc.
GitHub Repository
Company clustering with K-means/GMM and visualization with PCA, t-SNE, using SSAN relation extraction

RE results graph visualization and company clustering Installation pip install -r requirements.txt python -m nltk.downloader stopwords python3.7 main.

Jieun Han 1 Oct 06, 2022
PyTorch implementation of MoCo: Momentum Contrast for Unsupervised Visual Representation Learning

MoCo: Momentum Contrast for Unsupervised Visual Representation Learning This is a PyTorch implementation of the MoCo paper: @Article{he2019moco, aut

Meta Research 3.7k Jan 02, 2023
Code for the paper "Attention Approximates Sparse Distributed Memory"

Attention Approximates Sparse Distributed Memory - Codebase This is all of the code used to run analyses in the paper "Attention Approximates Sparse D

Trenton Bricken 14 Dec 05, 2022
ICNet for Real-Time Semantic Segmentation on High-Resolution Images, ECCV2018

ICNet for Real-Time Semantic Segmentation on High-Resolution Images by Hengshuang Zhao, Xiaojuan Qi, Xiaoyong Shen, Jianping Shi, Jiaya Jia, details a

Hengshuang Zhao 594 Dec 31, 2022
Open-source implementation of Google Vizier for hyper parameters tuning

Advisor Introduction Advisor is the hyper parameters tuning system for black box optimization. It is the open-source implementation of Google Vizier w

tobe 1.5k Jan 04, 2023
LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data

LSTM Neural Network for Time Series Prediction LSTM built using the Keras Python package to predict time series steps and sequences. Includes sine wav

Jakob Aungiers 4.1k Jan 02, 2023
A scikit-learn-compatible module for estimating prediction intervals.

MAPIE - Model Agnostic Prediction Interval Estimator MAPIE allows you to easily estimate prediction intervals (or prediction sets) using your favourit

588 Jan 04, 2023
🔮 Execution time predictions for deep neural network training iterations across different GPUs.

Habitat: A Runtime-Based Computational Performance Predictor for Deep Neural Network Training Habitat is a tool that predicts a deep neural network's

Geoffrey Yu 44 Dec 27, 2022
Space-event-trace - Tracing service for spaceteam events

space-event-trace Tracing service for TU Wien Spaceteam events. This service is

TU Wien Space Team 2 Jan 04, 2022
Annealed Flow Transport Monte Carlo

Annealed Flow Transport Monte Carlo Open source implementation accompanying ICML 2021 paper by Michael Arbel*, Alexander G. D. G. Matthews* and Arnaud

DeepMind 30 Nov 21, 2022
Small utility to demangle Nim symbols in callgrind files

nim_callgrind A small utility to demangle Nim symbols from callgrind files. Usage Run your (Nim) program with something like this: valgrind --tool=cal

kraptor 3 Feb 15, 2022
TransNet V2: Shot Boundary Detection Neural Network

TransNet V2: Shot Boundary Detection Neural Network This repository contains code for TransNet V2: An effective deep network architecture for fast sho

Tomáš Souček 212 Dec 27, 2022
This is the repo for the paper `SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization'. (published in Bioinformatics'21)

SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization This is the code for our paper ``SumGNN: Multi-typed Drug

Yue Yu 58 Dec 21, 2022
Accompanying code for the paper "A Kernel Test for Causal Association via Noise Contrastive Backdoor Adjustment".

#backdoor-HSIC (bd_HSIC) Accompanying code for the paper "A Kernel Test for Causal Association via Noise Contrastive Backdoor Adjustment". To generate

Robert Hu 0 Nov 25, 2021
Winning solution of the Indoor Location & Navigation Kaggle competition

This repository contains the code to generate the winning solution of the Kaggle competition on indoor location and navigation organized by Microsoft

Tom Van de Wiele 62 Dec 28, 2022
Determined: Deep Learning Training Platform

Determined: Deep Learning Training Platform Determined is an open-source deep learning training platform that makes building models fast and easy. Det

Determined AI 2k Dec 31, 2022
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

Bayesian Neural Networks Pytorch implementations for the following approximate inference methods: Bayes by Backprop Bayes by Backprop + Local Reparame

1.4k Jan 07, 2023
Fast RFC3339 compliant Python date-time library

udatetime: Fast RFC3339 compliant date-time library Handling date-times is a painful act because of the sheer endless amount of formats used by people

Simon Pirschel 235 Oct 25, 2022
Code of 3D Shape Variational Autoencoder Latent Disentanglement via Mini-Batch Feature Swapping for Bodies and Faces

3D Shape Variational Autoencoder Latent Disentanglement via Mini-Batch Feature Swapping for Bodies and Faces Installation After cloning the repo open

37 Dec 03, 2022
DLWP: Deep Learning Weather Prediction

DLWP: Deep Learning Weather Prediction DLWP is a Python project containing data-

Kushal Shingote 3 Aug 14, 2022