|
from statistics import mean |
|
import pandas as pd |
|
from datasets import load_dataset |
|
|
|
data = load_dataset("cardiffnlp/relentless", split='test') |
|
|
|
cor = [] |
|
for d in data: |
|
true_rank = sorted(d['ranks']) |
|
corr_tmp = [] |
|
for a in range(7): |
|
single_pred = [x[a] for x in d['scores_all']] |
|
rank_map = {p: n for n, p in enumerate(sorted(single_pred), 1)} |
|
single_pred = [rank_map[p] for p in single_pred] |
|
|
|
pred = [mean(_x for n, _x in enumerate(x) if n != a) for x in d['scores_all']] |
|
rank_map = {p: n for n, p in enumerate(sorted(pred), 1)} |
|
pred = [rank_map[p] for p in pred] |
|
|
|
corr_tmp.append(pd.DataFrame([single_pred, pred]).T.corr("spearman").values[1][0]) |
|
cor.append({"relation": d['relation_type'], "Avg.\ of others": mean(corr_tmp)}) |
|
|
|
df = pd.DataFrame(cor) |
|
df.index = df.pop("relation").values |
|
df = df.sort_index() |
|
df = df.T |
|
df['average'] = df.mean(axis=1).round(1) |
|
print(df.to_markdown()) |
|
print(df.to_latex()) |
|
df.to_csv("results/oracle.csv") |
|
|