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Merge pull request #2581 from ygorshenin/fix-scoring-model-script

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[search][quality] Fixed IR SVM implementation.
This commit is contained in:
mpimenov 2016-03-29 12:35:37 +03:00
commit f4f4f2dd9b
1 changed files with 9 additions and 2 deletions
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11
search/search_quality/scoring_model.py
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@ -9,7 +9,7 @@ import numpy as np
import pandas as pd
import sys
FEATURES = ['DistanceToPivot', 'Rank', 'NameScore', 'SearchType']
FEATURES = ['DistanceToPivot', 'Rank', 'NameScore', 'NameCoverage', 'SearchType']
DISTANCE_WINDOW = 1e9
MAX_RANK = 255
@ -122,11 +122,18 @@ def transform_data(data):
n, total = len(group), 0
for _, (i, j) in enumerate(itertools.combinations(range(n), 2)):
y = np.sign(relevances.iloc[j] - relevances.iloc[i])
dr = relevances.iloc[j] - relevances.iloc[i]
y = np.sign(dr)
if y == 0:
continue
x = np.array(features.iloc[j]) - np.array(features.iloc[i])
# Need to multiply x by average drop in NDCG when i-th and
# j-th are exchanged.
x *= abs(dr * (1 / log(j + 2, 2) - 1 / log(i + 2, 2)))
# This is needed to prevent disbalance in classes sizes.
if y != k:
x = np.negative(x)
y = -y