Even when forced_splits is set, the threshold is chosen from the bin_upper_bounds.

[AnchorBlues]

In the lightgbm, each numerical variable is replaced with discrete bins, and the threshold for split is chosen from the upper bounds of bin(variable name bin_upper_bounds).
Even when forced_splits is set, the lightgbm decides the threshold like that.
As a result, an unexpected result occurs.

Environment info

Operating System:
Ubuntu 14.04.5 LTS, Trusty Tahr

CPU/GPU model:
cpu
Intel(R) Core(TM) i7-6800K CPU @ 3.40GHz

C++/Python/R version:

Python 3.6.6 (default, Oct 9 2018, 12:34:16)
[GCC 7.3.0] :: Anaconda, Inc. on linux

lightgbm version : newest version (merged the commit until the commit id ca4b666(new version for master branch (#1824))

source

data = load_breast_cancer()
x = data.data
y = data.target

np.random.seed(0)
# create a new feature that takes a value 0 or 1.
dummy = np.random.randint(0, 2, size=len(x)) 

x = np.c_[dummy, x]

# create json file that forces the tree to split by the dummy feature. threshold is 0.5.
s = """
{
    "feature": 0,
    "threshold": 0.5,
    "left": {
    },
    "right": {
    }
}
"""

with open("forced_splits-0.json", mode='w') as f:
    f.write(s)

# model training
model = lgb.LGBMClassifier(random_state=42, forced_splits="forced_splits-0.json", num_leaves=3)
model.fit(x, y)

# dump model
json_obj = model.booster_.dump_model(1)
trees = json_obj['tree_info']

# the first tree
tree = trees[0]

tree['tree_structure']

result

The json output of the first decision tree is as follows:

{'split_index': 0,
 'split_feature': 0,
 'split_gain': 5.158199787139893,
 'threshold': 1e+300,
 'decision_type': '<=',
 'default_left': True,
 'missing_type': 'None',
 'internal_value': 0,
 'internal_count': 569,
 'left_child': {'split_index': 1,
  'split_feature': 24,
  'split_gain': 57102.30078125,
  'threshold': 700.6500000000001,
  'decision_type': '<=',
  'default_left': True,
  'missing_type': 'None',
  'internal_value': 0.204333,
  'internal_count': 569,
  'left_child': {'leaf_index': 0,
   'leaf_value': 49.87522832525989,
   'leaf_count': 296},
  'right_child': {'leaf_index': 2,
   'leaf_value': 0.36087350821712294,
   'leaf_count': 273}},
 'right_child': {'leaf_index': 1,
  'leaf_value': 0.5021707657990948,
  'leaf_count': 295}}

In line 4, the threshold for split is 1e+300, not 0.5.

I investigated the cause of the problem.
The threshold for split is chosen from bin_upper_bounds, specifically, the minimum value that is greater than or equal to the threshold forced by forced_splits.
In this case, bin_upper_bounds = [1e-35, inf], so the value inf is chosen as a threshold for split.
That is because the minimum value in [1e-35, inf] that is greater than or equal to 0.5 is inf.
As a result, the lightgbm try to split the data using the threshold inf.

I hope that the data is splitted by the 0.5 if the threshold is set to 0.5 at forced_splits.

[guolinke]

it is not trivial as the contents of force-splits json should be used in bin mapper finding algorithm.

I think a better solution is to allow the pre-defined bin_upper_bounds.

[StrikerRUS]

@guolinke Should anything be done before 2.2.4 release here?

[StrikerRUS]

@guolinke

[guolinke]

@StrikerRUS As it is not trivial and not very critical, I think we can do it after v2.2.4.

[StrikerRUS]

Closed in favor of being in #2302. We decided to keep all feature requests in one place.

Welcome to contribute this feature! Please re-open this issue (or post a comment if you are not a topic starter) if you are actively working on implementing this feature.

[StrikerRUS]

Reopening this as we have open PR.

[StrikerRUS]

Implemented in #2325.