# %%
from config import Config
import pandas as pd

df = pd.read_csv('results/eval_results.csv')


import json
feature_importances = json.loads(df.iloc[0].mutable_feature_importances_from_learner)

sorted_df = df.sort_values(by='valid_ndcg_5', ascending=False)
sorted_df.head()
# %%

e8e32aab33fac0673ba9b5e2ae2eebaba0f9387c
<mask token>

<mask token>
sorted_df.head()

<mask token>
df = pd.read_csv('results/eval_results.csv')
<mask token>
feature_importances = json.loads(df.iloc[0].
    mutable_feature_importances_from_learner)
sorted_df = df.sort_values(by='valid_ndcg_5', ascending=False)
sorted_df.head()

from config import Config
import pandas as pd
df = pd.read_csv('results/eval_results.csv')
import json
feature_importances = json.loads(df.iloc[0].
    mutable_feature_importances_from_learner)
sorted_df = df.sort_values(by='valid_ndcg_5', ascending=False)
sorted_df.head()

# %%
from config import Config
import pandas as pd

df = pd.read_csv('results/eval_results.csv')


import json
feature_importances = json.loads(df.iloc[0].mutable_feature_importances_from_learner)

sorted_df = df.sort_values(by='valid_ndcg_5', ascending=False)
sorted_df.head()
# %%
