msrank
Load the Microsoft Learning to Rank Dataset.
The training dataset contains 723412 objects. Each object is described by 138 columns. The first column contains the label value, the second one contains the identifier of the object's group (GroupId). All other columns contain features.
The validation dataset contains 241521 objects. The structure is identical to the training dataset.
Method call format
msrank()
Type of return value
A two pandas.DataFrame tuple (for train and validation datasets).
Usage examples
from catboost.datasets import msrank
msrank_train, msrank_test = msrank()
print(msrank_train.head(3))
The output of this example:
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 ... 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137
0 2.0 1.0 3.0 3.0 0.0 0.0 3.0 1.0 1.0 0.0 0.0 1.0 156.0 4.0 0.0 ... -4.474452 -23.634899 -28.119826 -13.581932 3.0 62.0 11089534.0 2.0 116.0 64034.0 13.0 3.0 0.0 0.0 0.0
1 0.0 1.0 3.0 0.0 3.0 0.0 3.0 1.0 0.0 1.0 0.0 1.0 168.0 3.0 10.0 ... -24.041386 -7.222766 -28.119826 -12.483964 2.0 44.0 5.0 30.0 23836.0 63634.0 2.0 4.0 0.0 0.0 0.0
2 0.0 1.0 3.0 0.0 3.0 0.0 3.0 1.0 0.0 1.0 0.0 1.0 674.0 1.0 4.0 ... -24.041386 -4.474536 -28.119826 -15.288797 3.0 59.0 5.0 8.0 213.0 48469.0 1.0 13.0 0.0 0.0 0.0
[3 rows x 138 columns]