Update dataset monotonic1.
Fix nans in last row.
Encode cat features sequentially.
Restore initial target.
@@ -159,7 +159,7 @@ def epsilon():
def monotonic1():
"""
Yandex internal dataset with monotonic constraints.
- Can be used for regression.
+ Can be used for poisson regression.
Has several numerical and several categorical features.
The first column contains target values. Columns with names Cat* contain categorical features.
Columns with names Num* contain numerical features.
@@ -170,9 +170,9 @@ def monotonic1():
for a monotonic negative feature M, such that x1[M] > x2[M], then the following inequality must
hold for predictions: f(x1) <= f(x2)
"""
- url = 'https://storage.mds.yandex.net/get-devtools-opensource/233854/monotonic1.tar.gz'
- md5 = '4d9bf62372afd44feb0842fa8b4ed058'
- dataset_name, train_file, test_file = 'monotonic1', 'train.csv', 'test.csv'
+ url = 'https://storage.mds.yandex.net/get-devtools-opensource/479623/monotonic1.tar.gz'
+ md5 = '1b9d8e15bc3fd6f1498e652e7fc4f4ca'
+ dataset_name, train_file, test_file = 'monotonic1', 'train.tsv', 'test.tsv'
return _cached_dataset_load_pd(url, md5, dataset_name, train_file, test_file, sep='\t')
