163eb7df13667e21b0e02a2706e18d1f53eee610,skrebate/iterrelief.py,IterRelief,fit,#IterRelief#,69
Before Change
weight_history.append(feature_weights)
feature_weights = [(x - mn)/(rg) for x in feature_weights]
distance_weights += feature_weights
After Change
if iteration == 0:
no_diff = False
else:
for i in range(len(feature_weights)):
//previous array of feature_weights
prev = weight_history[len(weight_history)-1]
diff = abs(prev[i] - feature_weights[i])
// first encounter of value that has difference greater than threshold, set no_diff to False, and break out of checking loop
if diff >= 0.0001:
no_diff = False
break;
if no_diff:
break;
mx = max(feature_weights)
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 7
Instances
Project Name: EpistasisLab/scikit-rebate
Commit Name: 163eb7df13667e21b0e02a2706e18d1f53eee610
Time: 2020-01-29
Author: alexmxu99@gmail.com
File Name: skrebate/iterrelief.py
Class Name: IterRelief
Method Name: fit
Project Name: maxpumperla/deep_learning_and_the_game_of_go
Commit Name: a17ac3677d207e04a53ed70fa971fbf436c0266f
Time: 2020-04-08
Author: 41198454+JingOY0610@users.noreply.github.com
File Name: code/dlgo/agent/alphago.py
Class Name: AlphaGoMCTS
Method Name: policy_rollout
Project Name: EpistasisLab/scikit-rebate
Commit Name: ece383696800b9b34854df27a65a3d1d74669952
Time: 2020-05-28
Author: alexmxu@alexs-mbp-3.attlocal.net
File Name: skrebate/iterrelief.py
Class Name: IterRelief
Method Name: fit