James McCool
commited on
Commit
·
200da18
1
Parent(s):
cdfb6e5
Comment out unnecessary column drops in predict_dupes.py to retain data for potential future use, enhancing flexibility in the duplicate prediction process.
Browse files
global_func/predict_dupes.py
CHANGED
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@@ -634,9 +634,9 @@ def predict_dupes(portfolio, maps_dict, site_var, type_var, Contest_Size, streng
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| 634 |
# Calculate similarity score based on actual player selection
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| 635 |
portfolio['Diversity'] = calculate_player_similarity_score_vectorized(portfolio, player_columns)
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| 636 |
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| 637 |
-
portfolio = portfolio.drop(columns=dup_count_columns)
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| 638 |
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portfolio = portfolio.drop(columns=own_columns)
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| 639 |
-
portfolio = portfolio.drop(columns=calc_columns)
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| 640 |
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| 641 |
int16_columns_stacks = ['Dupes', 'Size', 'salary']
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| 642 |
int16_columns_nstacks = ['Dupes', 'salary']
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# Calculate similarity score based on actual player selection
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| 635 |
portfolio['Diversity'] = calculate_player_similarity_score_vectorized(portfolio, player_columns)
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| 636 |
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| 637 |
+
# portfolio = portfolio.drop(columns=dup_count_columns)
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| 638 |
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# portfolio = portfolio.drop(columns=own_columns)
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| 639 |
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# portfolio = portfolio.drop(columns=calc_columns)
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| 640 |
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| 641 |
int16_columns_stacks = ['Dupes', 'Size', 'salary']
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| 642 |
int16_columns_nstacks = ['Dupes', 'salary']
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