Source code for cornac.datasets.tradesy

# Copyright 2018 The Cornac Authors. All Rights Reserved.
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"""
Link to the data: http://jmcauley.ucsd.edu/data/tradesy/
This data is used in the VBPR paper. After cleaning the data, we have:
- Number of feedback: 394,421 (410,186 is reported but there are duplicates)
- Number of users:     19,243 (19,823 is reported due to duplicates)
- Number of items:    165,906 (166,521 is reported due to duplicates)
"""

from typing import List

import numpy as np

from ..utils import cache
from ..data import Reader
from ..data.reader import read_text


[docs]def load_data(reader: Reader = None) -> List: """Load the feedback observations Parameters ---------- reader: `obj:cornac.data.Reader`, default: None Reader object used to read the data. Returns ------- data: array-like Data in the form of a list of tuples (user, item, 1). """ fpath = cache(url='https://static.preferred.ai/cornac/datasets/tradesy/users.zip', unzip=True, relative_path='tradesy/users.csv') reader = Reader() if reader is None else reader return reader.read(fpath, fmt='UI', sep=',')
[docs]def load_feature(): """Load the item visual feature Returns ------- features: numpy.ndarray Feature matrix with shape (n, 4096) with n is the number of items. item_ids: List List of item ids aligned with indices in `features`. """ features = np.load(cache(url='https://static.preferred.ai/cornac/datasets/tradesy/item_features.zip', unzip=True, relative_path='tradesy/item_features.npy')) item_ids = read_text(cache(url='https://static.preferred.ai/cornac/datasets/tradesy/item_ids.zip', unzip=True, relative_path='tradesy/item_ids.txt')) return features, item_ids